FORM 51-102F3
MATERIAL CHANGE REPORT

SCHEDULE A
DEL TORO
MINERAL RESOURCE AND MINERAL RESERVE ESTIMATES

Mineral Resource Estimates

Mineral Resource estimation at Del Toro was performed on four vein systems within three mining operations and three exploration veins:

• Mina Dolores: inclusive of Santa Teresa, Santa Teresa de Alto, Santa Teresa de Bajo, Purisima and Dolores;

• Mina Perseverancia: inclusive of San Nicolas and Escondida;

• Mina San Juan: inclusive of Lupitas, Lupitas Alto, San Jose and San Jose Alto, Cuerpo 1, Cuerpo 2 and Cuerpo 3;

• Zaragoza; and

• Carmen and Consuelo.

These were grouped into three estimation areas:

• Mina Dolores, Perseverancia, San Juan-Lupitas;

• Mina San Juan Cuerpo 3; and

• Minor veins (Cuerpo 1 (A, B and C), Cuerpo 2, Escondida, Zaragoza, Carmen, and Consuelo).

Depending on the mine and model, resource estimation is based on information such as the current drill hole database, channel sampling, underground level mapping, and digitized data for underground drifts and stopes. Specific gravity (SG) data were typically assigned based on major rock type groups or on domains.

Where computerized modelling techniques were employed, geological and mineralized vein solids were constructed. Assay, density and waste samples were composited, with composite lengths variable depending on domain. High-grade outlier samples were capped, or an outlier-restriction influence radius was applied. Domain boundaries were reviewed, and, typically, hard boundaries were implemented for estimation. Where sufficient data were available, semi-variogram models were developed from the composite samples for variables such as silver, arsenic, gold, lead, and zinc.

Estimation of silver, gold, lead, zinc, and arsenic within the Mina Dolores, Perseverancia and San Juan-Lupitas domains was undertaken using a two-dimensional (2D) compositing and estimation approach. A combination of estimation methodologies was used within the estimate to allow for interpolation where limited composite data and unstable variogram models were not able to capture the spatial continuity required for Ordinary Kriging (OK).

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Estimation of silver, gold, lead, zinc, and arsenic for the Cuerpo 3 deposit was completed using OK. Blocks within the Cuerpo 3 model were estimated with two successive interpolation passes for all metals. The estimates were validated using a combination of methods, including visual inspection, comparison of block grade distributions with drill hole composite sample grades using scatter and cumulative probability plots, and comparison of average composite sample values with average estimated block grades using swath plots. In general, the authors found the estimates to be unbiased, and to provide a fair representation of the supporting composite data. A range of criteria were considered when addressing the suitability of the classification boundaries for the Mineral Resource estimates, which could include some or all of the following: confidence in the interpretation of the geological continuity and volume of mineralized zones, drill spacing and sampling quality, recent mining activity, continuity of silver grades defined from variogram models, estimation technique, number of samples used to estimate a block, average composite distances, the number of octants required to estimate a block, and kriging quality parameters. No Measured Mineral Resources were estimated for Cuerpo 3.

For the estimates using polygonal methods, longitudinal sections of vein structures were constructed. Once the projections for Measured, Indicated, and Inferred polygons were addressed, the area, average width, volume, and weighted mean grade were calculated for every polygon. Outlier grades were capped. Polygons of Measured Mineral Resources are projected vertically (up and down) 20 m away from mine levels informed by chip samples. Indicated Mineral Resources are projected 20 additional metres from Measured Mineral Resources away from mine levels and 20 m around drill hole intercepts where there is continuity of mineralization as indicated by drilling information or by mine levels with sample lines reporting potentially economic grades. Inferred Mineral Resources are projected 50 m from drill hole intercepts or polygons of indicated Mineral Resources. In most cases, Inferred Mineral Resources are projected 20 m beyond Indicated Mineral Resources. Drill hole spacing varies generally from 15 to 75 m in zones of Measured and Indicated Mineral Resources, whereas chip sample lines are spaced between 1.5 and 3.0 m in those mine levels with Measured or Indicated Mineral Resources.

Mineral Resources are reported using silver-equivalent (Ag-Eq) cut-off grades, where Ag-Eq is calculated as:

• Ag-Eq = Ag Grade + [(Au Grade x Au Recovery x Au Payable x Au Price / 31.1035) + (Pb Grade x Pb Recovery x Pb Payable x Pb Price x 2204.62) + (Zn Grade x Zn Recovery x Zn Payable x Zn Price x 2204.62)] / (Ag Recovery x Ag Payable x Ag Price / 31.1035)

Assumptions used to generate the cut-off grade common to all estimates included:

• Metal prices of $19.00 /oz Ag, $1,300.00 /oz Au, $1.00 /lb Pb and $1.20 /lb Zn;

• Actual and budgeted operating and sustaining costs;

• Metallurgical recovery for sulphides of 82% for Ag, 80% for Au, 67% for Pb and 15% for Zn; and

• Metals payable of 95% for Ag, Au and Pb and 85% for Zn in concentrates produced from sulphide minerals.

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A cut-off assumption of 120 g/t Ag-Eq was used for the Mina Dolores, Perseverancia, San Juan-Lupitas estimates, and a cut-off of 195 g/t Ag-Eq was used for Cuerpo 3 and the minor vein estimates.

Mineral Resource Statements

Mineral Resources are reported using the 2014 CIM Definition Standards for Mineral Resources and Mineral Reserves (2014 CIM Definition Standards), as summarized in Table 1-1 (Measured and Indicated Mineral Resources) and Table 1-2 (Inferred Mineral Resources).

Table 1-1: Measured and Indicated Mineral Resource Summary Table

Table 1-2: Inferred Mineral Resource Summary Table

Notes:
1.             Mineral Resources were prepared by the Company, SRK Consulting (Canada) Inc and Entech. The Qualified Person for the estimate is Jesus M. Velador Beltran, MMSA, QP, an employee of the Company.
2.             Measured and Indicated Mineral Resources are reported inclusive of Mineral Reserves. Mineral Resources have an effective date of December 31st, 2016. Mineral Resources that are not Mineral Reserves do not have demonstrated economic viability.
3.             Mineral Resources are reported above a silver-equivalent grade of 195 g/t Ag-Eq for Cuerpo 3 and 120 g/t Ag-Eq for all other veins. Silver equivalent was calculated using the equation Ag-Eq (g/t) = Ag (g/t) + Au (g/t) * 66.5 + Pb (%) * 29.6 + Zn (%) * 7.1. Assumptions include metal prices of $19.00 /oz Ag, $1,300 /oz Au, $1.00 /lb Pb and $1.20 /lb Zn; metallurgical recoveries of 82% for Ag, 80% for Au, 67% for Pb and 15% for Zn; and metal payability of 95% for Ag, Au and Pb, and 85% for Zn in concentrates produced from all materials.
4.             Numbers have been rounded as required by reporting guidelines. Totals may not sum due to rounding.

The Mineral Resources may be impacted by additional infill and exploration drilling that may identify additional mineralization or cause changes to the current domain shapes and geological assumptions. The Mineral Resources may also be affected by subsequent assessments of mining, environment, processing, permitting, taxation, socio-economics, and other factors.

Mineral Reserve Estimates

Mineral Reserves were initially constrained using Ag-Eq cut-off grades developed for each mining method used. The cut-off grades considered were:

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• Fully Costed Cut-Off Grade (FCOG) – a grade of material in which recoverable value pays for all associated costs, including but not limited to development, stoping, processing, treatment, and all administration costs. For high-level assessments, the Company allows for some capital in the determination (sustaining capital);

• Incremental Cut-Off Grade (ICOG) – a grade of material in which recoverable value pays for stoping, processing, treatment, and administration (if the material adds to mine life). Development and sustaining capital are excluded under the premise that these costs have already been absorbed by material deemed economic by the consideration of the FCOG; and

• Marginal Cut-Off Grade (MCOG) – a grade of material in which recoverable value pays for the incremental haulage cost between the waste dump and the processing facility, processing costs (variable component) and administration costs (if mine life is extended).

Considerations of ore loss and dilution for each mining method were then included:

• Cut-and-fill: 10% unplanned dilution, mining recovery of 95% (Dolores, San Juan, Perseverancia);

• Long-hole stoping: 15% unplanned dilution, mining recovery of 95% (Dolores);

• Development: 10% unplanned dilution, mining recovery of 95% (Dolores);

• Shrinkage stoping: 10% unplanned dilution, mining recovery of 95% (San Juan); and

• Drift-and-fill: 20% unplanned dilution, mining recovery of 90% (San Juan Cuerpo 3).

These considerations were then incorporated with the initial cut-off grade determinations to arrive at a final cut-off grade criteria set (Table 1-3). Stopes were then optimized based on selected mining methods and minimum stope widths.

Table 1-3: Final Cut-Off Grades Applied by Mining Method

Mineral Reserve estimates were based on mining modifying factors gathered from actual operations data as well as from estimates that follow industry best practices.

Modifying factors for mining were applied to the Measured and Indicated Mineral Resources on a stope-by-stope evaluation and have been determined suitable for conversion to Mineral Reserves. To convert from Mineral Resources to Mineral Reserves, the resource blocks were interrogated by applying economic criteria as well as geometric constraints based on the mining method envisioned. Mineable blocks or stopes were defined by following this process.

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Notes:
1.             The Qualified Person for the Mineral Reserve estimate is Ramon Mendoza Reyes, QP, an employee of the Company. Mineral Reserves have an effective date of 31 December, 2016.
2.             Mineral Reserves are defined using multiple variable cut-off grades, then stope designs are optimized based on selected mining methods and minimum stope widths. Mining methods will include cut-and-fill (resue), drift-and-fill, shrinkage stoping and longhole stoping with cemented fill methods.
3.             The Ag-Eq grade formula used was Ag-Eq Grade = Ag Grade + [(Au Grade * Au Recovery * Au Payable * Au Price / 31.1035) + (Pb Grade * Pb Recovery * Pb Payable * Pb Price * 22.0462) + (Zn Grade * Zn Recovery * Zn Payable * Zn Price * 22.0462)] / (Ag Recovery * Ag Payable * Ag Price / 31.1035) .
4.             Key assumptions and parameters include: Metal price of US$18/oz Ag, US$1.00/lb Pb, US$1.15/lb Zn, US$1,250/oz Au; metallurgical recoveries of 82.3% for Ag, 67.5% for Pb, 15.0% for Zn, 60.0% for Au; metal payabilities of 95% for Ag, Pb and Au, and 85% for Zn; direct costs of US$49.3/t mill feed, process and treatment costs of US$38.80/t mill feed and general and administration (indirect costs) of US$18.0/t. Ore loss and dilution is variable by mine, and by mining method. Mining recoveries range from 90–95%. Unplanned dilution assumptions range from 10–20%.
5.             Numbers have been rounded as required by reporting guidelines. Totals may not sum due to rounding.

Factors that could affect the Mineral Reserves include changes to the following assumptions: unplanned dilution, mining recovery, geotechnical conditions, equipment productivities, metallurgical recoveries, metal prices and exchange rates, mill throughput capacities, operating costs, and capital costs.

LIFE OF MINE

Production Plan

Del Toro has well-established productivities which were applied in the mine schedule, including the time taken to drill, blast, muck and support each round; vertical development considerations; longhole drilling; material movement; and backfill requirements. The following milife-of-mine assumptions are included in the schedule presented in Table 1-5:

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The combined Del Toro mine is projected to operate for a total of six years. Table 1-5: Mine Schedule

SCHEDULE B
LA PARILLA
MINERAL RESOURCE AND MINERAL RESERVE ESTIMATES

Mineral Resource Estimates

Mineral Resource estimates have been completed on the Quebradillas, San Nicolas, Rosarios, San Marcos, and Intermedia zones. Estimation at the San Marcos and Rosarios-Intermedia used ordinary kriging (OK); the remaining zones were estimated using polygonal methods. All currency is expressed as US$, unless noted otherwise.

San Marcos and Rosarios-Intermedia

A total of 79 drillholes (13,883 m) and 238 drillholes (51,020 m) were used for estimation at San Marcos and Rosarios-Intermedia, respectively. Wireframes were built for the mineralized veins using assay data. The weathering profile was modelled as a surface, using data collected from the underground operations. SRK chose a block size of 5 x 5 x 10 m for San Marcos and Rosarios-Intermedia.

Considering the relative thickness variation of the veins and the current mining approach of extracting the entire vein, all assays were composited to a single intersection per drillhole per vein, honouring the vein boundary. The impact of grade outliers was examined on composite data for each element using log probability plots and cumulative statistics. The three-dimensional location of the potential outlier values was also considered. A number of samples were capped in each zone. Specific gravity values were derived from wax-coated-water displacement method samples. Formulas were derived to estimate block density based on lead, zinc, and iron content.

SRK found that variograms modelled on lead yielded a reasonably clear continuity of long-range structures, allowing fitting of variogram models. The lead variograms were applied to all other metals. However, the orientations were adjusted to match the azimuth and dip of the vein wireframes and other underground information, where applicable.

Due to their distinct geological identity, all veins were estimated independently, using a hard boundary. Three estimation passes were required, informed by capped composites. SRK assessed the sensitivity of the block estimates to changes in minimum and maximum number of data, use of octant search, and the number of informing drillholes. Results from these studies show that globally, the model is relatively insensitive to the selection of the estimation parameters and data restrictions.

The resource block model was validated by means of visual inspection of the OK results, checking the OK model against nearest neighbour and inverse distance algorithm (power of two) models, verifying that the global quantities and average grade for each metal from each method were reasonably comparable, and validating the block estimates against the declustered mean informing composite data.

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No Measured mineral resources were classified. Indicated mineral resources were classified for blocks estimated during the first estimation run considering full variogram ranges and having an estimated block grade above the reporting cut-off grade. Blocks estimated during the second and third pass considering search neighbourhoods set with more relaxed estimation parameters were classified as Inferred.

Quebradillas and San Nicolas

The polygonal estimates are supported by a combination of drillhole, channel and chip samples, and underground geological mapping. Longitudinal sections of vein structures were constructed. Polygons were projected from mine levels, or constructed around drill intercepts, and classified as Indicated or Inferred. No Measured mineral resource polygons were defined.

Polygons of Indicated mineral resources were projected vertically (up and down) 40 m from mine levels informed by channel and chip samples, and 20 m around drillhole intercepts where there is continuity of mineralization (based on drilling information or mine levels with sample lines reporting potentially economic grades). Inferred mineral resources were projected 50 m from drillhole intercepts or from polygons that have been classified as Indicated mineral resources. Polygons for Indicated and Inferred mineral resources were drawn on longitudinal sections using BRISCAD Pro V12 software, after which the area, average width, volume, and weighted mean grade were estimated. Grades were capped following analysis of cumulative frequency histograms; the grade at the 95th percentile was selected as the cap point. An average SG of 2.7 was used to estimate tonnages.

Mineral resources are reported using the considerations in Table 1-1.

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Table 1-1: Considerations used for reasonable prospects for eventual economic extraction (First Majestic Silver Corp., 2017)

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Mineral Resource Summary

Indicated and Inferred mineral resources are summarized in Table 1-2.

The resource estimation based on block modelling techniques for San Marcos and Rosarios-Intermedia were completed by Mr. Sébastien Bernier, PGeo (APGO #1847), of SRK Consulting (Canada) Inc. Mr. Bernier is the Qualified Person taking responsibility for the mineral resource estimates based on block modelling technicques.

The estimates for Quebradillas and San Nicolas using polygonal methods were completed under supervision of Mr. Jesús M. Velador Beltrán, MMSA, and Director of Exploration for the Company. Mr. Velador reviewed the polygonal estimates, and is the Qualified Person taking responsibility for the mineral resource estimates based on polygonal methods.

Mineral resources are reported inclusive of mineral reserves and have an effective date of December 31, 2016. Mineral resources that are not mineral reserves do not have demonstrated economic viability.

Estimates are reported using silver equivalent (Ag-Eq) cut-off grades that were calculated using the formula:

Ag-Eq = Ag Grade + [ (Au Grade x Au Recovery x Au Payable x Au Price / 31.1035) + (Pb Grade x Pb Recovery x Pb Payable x Pb Price x 2204.62) + (Zn Grade x Zn Recovery x Zn Payable x Zn Price x 2204.62)] / (Ag Recovery x Ag Payable x Ag Price / 31.1035) .

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Table 1-2: Mineral Resource Summary*, La Parilla Mine, Mexico, with an Effective Date of December 31, 2016 (First Majestic Silver Corp., 2017)

*
(1) Block model estimates prepared under the supervision of Sebastien Bernier, PGeo, Principal Consultant (Geology), SRK Consulting (Canada) Inc.
(2) Update polygonal estimates prepared under the supervision of Jesus M. Velador Beltran, MMSA, QP Geology for First Majestic Silver Corp.
(3) Mineral resources have been classified in accordance with the Canadian Institute of Mining, Metallurgy and Petroleum ("CIM") Definition Standards on Mineral Resources and Mineral Reserves, whose definitions are incorporated by reference into NI 43-101
(4) Metal prices considered were $19.00 /oz Ag, $1,300 /oz Au, $1.00 /lb Pb and $1.20 /lb zinc.
(5) Cut-off grade considered for oxide block model estimates from underground operation was 130 g/t Ag-Eq, based on actual costs excluding sustaining costs.
(6) Cut-off grade considered for sulphides block model estimates was 135 g/t Ag-Eq, based on actual costs excluding sustaining costs.
(7) Cut-off grade considered for oxide polygonal estimates from underground operation was 160 g/t Ag-Eq and 95 g/t Ag-Eq for open pit operations, both are based on actual and budgeted operating and sustaining costs.
(8) Cut-off grade considered for sulphides polygonal estimates was 155 g/t Ag-Eq and is based on actual and budgeted operating and sustaining costs.
(9) Metallurgical recovery used for oxides based on 2016 actuals was 65.9% for silver and 80.8% for gold.
(10) Metallurgical recovery used for sulphides based on 2016 actuals was 86.6% for silver, 80% for gold, 82.5% for lead, and 64.2% for zinc.
(11) Metal payable used was 99.6% for silver and 95% for gold in doré produced from oxides.
(12) Metal payable used was 95% for silver, gold, and lead and 85% for zinc in concentrates produced from sulphides.
(13) Silver equivalent grade is estimated as: Ag-Eq = Ag Grade + [ (Au Grade x Au Recovery x Au Payable x Au Price / 31.1035) + (Pb Grade x Pb Recovery x Pb Payable x Pb Price x 2204.62) + (Zn Grade x Zn Recovery x Zn Payable x Zn Price x 2204.62)] /(Ag Recovery x Ag Payable x Ag Price / 31.1035) .
(14) Tonnage is expressed in thousands of tonnes, metal content is expressed in thousands of ounces or thousands of tonnes.
(15) Totals may not add up due to rounding.
(16) Measured and Indicated Mineral resources are reported inclusive or Mineral reserves.

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The Mineral resources may be impacted by additional infill and exploration drilling that may identify additional mineralization or cause changes to the current domain shapes and geological assumptions. The Mineral resources may also be affected by subsequent assessments of mining, processing, environment, permitting, taxation, socio-economic, and other factors.

Mineral Reserve Estimates

Mineral Reserves Estimated from Mineral Resources Based on Block Models

Mineral reserve estimates were developed separately for both oxide and sulphide ores with the majority of the assumptions and modifying factors being the same for both types. Zones estimated using block modelling methods included Rosarios, Intermedia, and San Marcos. Mineral reserves were separately estimated for each deposit and mineralization type.

Table 1-3 summarizes the key assumptions and modifying factors used in underground mineral reserve estimation for the sulphide and oxide ores.

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Table 1-3: Assumptions and modifying factors used in mineral reserve estimation (First Majestic Silver Corp., 2017)

** Pb and Zn concentrate treatment and refining charges, penalties, price participation, freight, insurance and representation NSR values were used as an indicator to determine if a mining shape met the economic cut-off criteria for inclusion into the mining plan. NSR formulas for both oxide and sulphide mineralization are based on the assumptions listed above and coded into the block models.

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The NSR formula for oxide ores can be expressed as:

• NSR (US$/tonne milled) = $0.38 x Ag + $30.85 x Au – $1.19

Where:

• Ag is the silver grade in g/t.

• Au is the gold grade in g/t.

• $1.19 per tonne milled represents the fixed costs for refining charges, freight, insurance, and representation.

The NSR formula for sulphide ores (adding the contributions from the lead concentrate and zinc concentrate) can be expressed as:

• NSR (US$/tonne milled) = $0.42 x Ag + $7.15 x Au + $16.97 x Pb + $13.22 x Zn – $17.29

Where:

• Ag is the silver grade in g/t.

• Au is the gold grade in g/t.

• Pb is the lead grade in percent.

• Zn is the zinc grade in percent.

• $17.29/t milled represents the fixed costs for treatment charges, price participation, penalties, freight, insurance, and representation for both concentrates.

As some of the potential mineral reserves are located in areas in proximity to existing development, and some are located in new mining areas, a two-tier cut-off value (COV) was used:

• A COV excluding sustaining development and diamond drilling costs was applied to the areas that are already developed.

• A COV including sustaining development and diamond drilling costs was applied to any new areas requiring ramp development and infill diamond drilling before mining could begin.

The COV for sulphide ore, without sustaining development and drilling costs was US$56.46, and including those costs was US$63.51. The costs for oxide ore were US$52.73 (without sustaining costs) and US$59.78 (with sustaining costs).

The stope designs targeted only Measured and Indicated mineral resources, but where Inferred mineral resources were unavoidably included within mining shapes, they were treated in the same manner as external dilution. This was achieved by setting the NSR value of all Inferred mineral resource blocks to equal the off-site costs, i.e. the NSR value of all Inferred mineral resource blocks is negative. Total Inferred mineral resources included in the mineral reserve estimate from block models is less than 2%.

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Variables such as sub-level spacing, sill pillar sizing, and minimum mining width were based on current mining practices at site.

The final stope shapes were processed using Datamine Studio 5D Planner software to evaluate the tonnes and grade by mineral resource category. These evaluation results represent the in-situ mineral resources available to be mined. The evaluation results were imported into Microsoft Excel in order to apply the modifying factors and compile the final mineral reserve estimate for the deposits based on block models. The modifying factors applied to the evaluation results were external dilution and mining recovery. Internal dilution is already accounted for within the 3D stope shapes and is included in the evaluation results. Dilution percentages are defined as waste tonnes/ore tonnes (W/O) in all cases.

External dilution on the mineral reserves averages 22% for oxides and 15% for sulphides. The external dilution is based on the true width of the vein, with a constant overbreak added to estimate the final mining width to be broken. For oxide ores, the minimum mining width possible using resuing is 0.9 m + 0.4 m of overbreak, or 1.3 m. As the sulphide ores are not as friable as the oxide ores, the minimum mining width for sulphides is 0.9 m + 0.3 m overbreak, or 1.2 m. An additional 5% external dilution was added to account for dilution from other sources, such as backfill dilution from mucking operations. Mining recovery for mechanized cut and fill stopes was set at 95%.

Mineral Reserves Estimated from Mineral Resources Based on Polygons

Mineral reserve estimates were developed separately for both oxide and sulphide ores, with the majority of the assumptions and modifying factors being the same for both types where mined by underground methods. Zones estimated using polygonal methods were the Quebradillas and San Nicolas areas.

The polygon-derived estimates use the same assumptions as presented in Table 1-3 for the block-model derived estimates.

A silver equivalent (Ag-Eq) cut-off grade (COG) was estimated to identify the polygons that complete La Parrilla’s initial mine design and initiate the process of underground mine optimization. The all-in-sustaining mining cost for mining underground oxide material was $59.78/t and the cost for mining underground sulphide material was $63.51/t; these figures include sustaining development and sustaining capital costs. The all-in-sustaining mining cost for mining oxide material using open pit methods is $37.33/t; this figure includes sustaining capital and sustaining waste stripping cost. The Ag-Eq cut-off used for mineral reserves reporting is based on 2016 actual costs. A COG of 100 g/t Ag-Eq was used for remnant oxide open pit material, and a cut-off grade of 160 Ag-Eq was used for both oxide and sulphide material to be mined using underground methods.

The polygon-derived estimates for material to be mined from underground use similar stope designs, external dilution, and mining recovery assumptions to that block-model derived estimates.

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For the open pit estimates, an average of 15% external dilution was considered for open pit mining to account for blasting overbreak. An additional 5% external dilution was added to account for dilution from other sources, such as waste dilution from surface loading and handling. Mining recovery for open pit mining was set at 95%.

Mineral Reserve Summary

The Mineral Reserve Summary for La Parrilla is provided as Table 1-4.

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Table 1-4: Mineral Reserve Summary*, La Parrilla Silver Mine, Mexico, with an Effective Date of December 31, 2016 (First Majestic Silver Corp., 2017)

*
(1) Block model estimates prepared under the supervision of Stephen Taylor, PEng, Principal Consultant (Mining), SRK Consulting (Canada) Inc.
(2) Update polygonal estimates prepared under the supervision of Ramóon Mendoza Reyes, PEng, QP Mining for First Majestic Silver Corp.
(3) Mineral reserves have been classified in accordance with the Canadian Institute of Mining, Metallurgy and Petroleum ("CIM") Definition Standards on Mineral Resources and Mineral Reserves, whose definitions are incorporated by reference into NI 43-101
(4) Metal prices considered for mineral reserves estimates were $18.00 /oz Ag, $1250 /oz Au, $1.00 /lb Pb, and $1.15 /lb Zn
(5) Metallurgical recovery used for oxides based on 2016 actuals was 65.9% for silver and 80.8% for gold.
(6) Metallurgical recovery used for sulphides based on 2016 actuals was 86.6% for silver, 80% for gold, 82.5% for lead, and 64.2% for zinc.
(7) Metal payable used was 99.6% for silver and 95% for gold in doré produced from oxides.
(8) Metal payable used was 95% for silver, gold, and lead and 85% for zinc in concentrates produced from sulphides.
(9) Silver equivalent grade is estimated as: Ag-Eq = Ag Grade + [ (Au Grade x Au Recovery x Au Payable x Au Price / 31.1035) + (Pb Grade x Pb Recovery x Pb Payable x Pb Price x 2204.62) + (Zn Grade x Zn Recovery x Zn Payable x Zn Price x 2204.62) ] / (Ag Recovery x Ag Payable x Ag Price / 31.1035) .
(10) The modifying factors used are consistent for each estimation method, but different for each ore type as described in Table 1-3.
(11) Cut-off NRS values considered for oxide block model estimates from underground operation was US$63.51 with sustaining costs and $US56.46 without sustaining costs, based on actual costs.
(12) Cut-off NSR values considered for sulphides block model estimates from underground operations was US$59.78 with sustaining costs and US$52.73 without sustaining costs, based on actual costs.
(13) Cut-off grade considered for oxide polygonal estimates from underground operation was 160 g/t Ag-Eq and 100 g/t Ag-Eq for open pit operations, both are based on actual and budgeted operating and sustaining costs.
(14) Cut-off grade considered for sulphides polygonal estimates was 160 g/t Ag-Eq and is based on actual and budgeted operating and sustaining costs.
(15) The mineral reserves information provided above for deposits based on block models represent an independent estimate prepared as of December 31, 2016. The information provided was reviewed and validated by Mr. Stephen Taylor, PEng of SRK Consulting (Canada) Inc, who has the appropriate relevant qualifications, and experience in mining and reserve estimation practices.
(16) The Mineral Reserves information provided above for deposits based on polygonal estimation techniques is based on internal estimates prepared as of Dec 31, 2016. The information provided was reviewed and validated by the Company's internal Qualified Person, Mr. Ramón Mendoza Reyes, PEng, who has the appropriate relevant qualifications, and experience in mining and reserve estimation practices.
(17) Tonnage is expressed in thousands of tonnes; metal content is expressed in thousands of ounces or thousands of tonnes.
(18) Totals may not add up due to rounding.

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LIFE OF MINE

The following underground areas will be mined in the life-of-mine plan at La Parrilla:

A basic development and production schedule was developed based on site mine design standards and previous performance metrics for production and development to track and report development metres and stope production for both oxide and sulphide ore types on a monthly basis. Based on the current life of mine plan, the Company will develop a total of 5–7 km of lateral waste development per year for three years, dropping to 1 km in the last year of production. The life-of-mine total is 19.6 km of lateral waste development including 11.3 km of capital development and 8.3 km of operating development. Capital vertical waste development totals 3.4 km. The overall production schedule shown in Table 1-5.

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Table 1-5: Underground Life-of-mine production schedule (First Majestic Silver Corp., 2017)

SCHEDULE C
SAN MARTIN
MINERAL RESOURCE AND MINERAL RESERVE ESTIMATES

Mineral Resource Estimates

Mineral Resource estimation was performed on a vein system consisting of 13 vein zones. Three vein zones (Intermedia, Pitayo and Hedionda or IPH) were estimated by Entech under supervision of the Company; four vein zones (Rosario, La Veladora, La Lima, and Huichola Norte or RVLH) were estimated by the Company using three-dimensional (3D) estimation methodologies, and six vein zones (Zuloaga, La Esperanza, Veta 420, Dique 690, La Blanca, and Despendimiento 7000, also referred to as the “Other Veins”) were estimated by the Company using two-dimensional (2D) or polygonal estimation. Different interpolation methodologies could be used depending on the vein’s geological and mineralization characteristics.

Intermedia, Pitayo, Hedionda, Rosario, La Lima, La Veladora and Huichola Norte Zones (IPHRVLH)

All available data, including drill holes, channel samples, level maps, and drill core photos, were used for geological solids modelling. Typically, however, only a high-quality data subset to support the estimates.

Exploratory data analysis was conducted prior to selecting the applicable composite interval. Composite lengths varied by vein, ranging from 1–2 m. Statistical and visual analyses were performed to validate the overall domain controls on mineralization and to ensure further domaining was not required. A metal sensitivity analysis was undertaken before any appropriate capping value was applied to composite files. All applied capping values were individually reviewed for each domain that was capped to ensure the reduction in metal was statistically appropriate and locally relevant.

Where sufficient data were available and as applicable to the final estimation methodology, semi-variograms were modelled. Bulk density values were derived from wax-coated-water displacement method samples, and an average bulk density value of 2.44 was used. Estimation methods included 2D and 3D compositing and estimation approaches. Interpolation methods included inverse distance weighting (IDW) to the third power (IDW3) and ordinary kriging (OK).

The resource block model was validated by visual comparison of composite grades against the block grades; statistical comparison of global declustered composite grade against estimated grade; and construction of swath plots along the long section axis of the domains, comparing declustered composite grades, estimated grades, number of composites, and tonnage estimated. A range of criteria was considered when addressing the suitability of the classification boundaries to the Mineral Resource estimates, and could include geological continuity and volume models; drill spacing and drill data quality; recent mining activity; modelling techniques; and estimation properties, including search strategy, number of composites and average distance of composites from blocks.

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A review of the estimates for reasonable prospects for eventual economic extraction was conducted, using considerations of metal pricing, silver-equivalent (Ag-Eq) cut-off grades (COG) based on site operating costs, metallurgical recoveries, and metals payability.

Zuloaga, La Esperanza, Veta 420, Dique 690, La Blanca, Desprendimiento 7000 (Other Veins)

In polygonal estimates, longitudinal sections of vein structures were constructed. Polygons were projected from mine levels, or constructed around drill intercepts, and classified as Indicated or Inferred. No Measured Mineral Resource polygons were defined.

Polygons of Indicated Mineral Resources are projected vertically (up and down) 45 m from mine levels informed by chip samples. Indicated Mineral Resources are projected 25 m around drill hole intercepts where there is continuity of mineralization, as indicated by drilling information or by mine levels with sample lines reporting potentially economic grades. Inferred Mineral Resources are projected 50 m from drill hole intercepts or polygons of Indicated Mineral Resources. In most cases, Inferred Mineral Resources are projected 20 m beyond Indicated Mineral Resources.

Grade capping was performed on a sample basis, prior to compositing, by length of channel line or drill hole intercept. An average bulk density value of 2.44 was used. The area, average width, volume, and weighted mean grade were calculated for every polygon.

A review of the estimates for reasonable prospects for eventual economic extraction was conducted, using considerations of metal pricing, silver Cut-off Grade (COG) based on site operating costs, metallurgical recoveries, and metals payability.

Mineral Resource Statement

Mineral Resources are reported per the following considerations:

• Metal prices considered were $19.00 /oz Ag and $1,300 /oz Au;

• The COG of 150 g/t Ag-Eq is based on actual and budgeted operating and sustaining costs, where Ag-Eq (g/t) = Ag (g/t) + Au (g/t) * 72.2;

• Metallurgical recovery used for oxide minerals was 83% for Ag and 87% for Au; and

• Metal payable used was 99.9% for Ag, and 99.85% for Au in doré produced from oxide minerals.

The Mineral Resources may be impacted by additional infill and exploration drilling that may identify additional mineralization or cause changes to the current domain shapes and geological assumptions. The Mineral Resources may also be affected by subsequent assessments of mining, processing, environment, permitting, taxation, socio-economics, and other factors.

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Measured and Indicated Mineral Resources are summarized in Table 1-1, and Inferred Mineral Resources in Table 1-2.

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Table 1-1: San Martín Consolidated Mineral Resource Summary, as at December 31, 2016

Notes:
1.             Mineral Resources for IPH were prepared by Entech. Mineral Resources for RVLH and Other Veins were prepared by the Company. The Qualified Person for the IPHRVLH estimate is Phillip J Spurgeon, P.Geo., and the Qualified Person for the Other Veins is Jesús M. Velador Beltrán, MMSA, both employees of the Company.
2.             Mineral Resources are reported inclusive of Mineral Reserves and have an effective date of December 31, 2016. Mineral Resources that are not Mineral Reserves do not have demonstrated economic viability.
3.             Mineral Resources are reported above a silver-equivalent grade of 150 g/t for IPHRVLH and above silver grade of 150 g/t for Other Veins. Silver equivalent grade is estimated as: Ag-Eq = Ag (g/t) + Au (g/t) * 72.2. Assumptions include metal prices of $19.00 /oz Ag and $1,300 /oz Au; metallurgical recoveries of 83% for Ag and 87% for Au; and metal payability of 99.9% for Ag and 99.85% for Au.
4.             Numbers have been rounded as required by reporting guidelines. Totals may not sum due to rounding.

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Table 1-2: Consolidated Inferred Mineral Resource Summary, as at December 31, 2016

Notes:
1.             Mineral Resources for IPH were prepared by Entech. Mineral Resources for RVLH and Other Veins were prepared by the Company. The Qualified Person for the IPHRVLH estimate is Phillip J Spurgeon, P.Geo., and the Qualified Person for the Other Veins is Jesús M. Velador Beltrán, MMSA, both employees of the Company.
2.             Mineral Resources are reported inclusive of Mineral Reserves and have an effective date of December 31, 2016. Mineral Resources that are not Mineral Reserves do not have demonstrated economic viability.
3.             Mineral Resources are reported above a silver-equivalent grade of 150 g/t for IPHRVLH and above silver grade of 150 g/t for Other Veins. Silver equivalent grade is estimated as: Ag-Eq = Ag (g/t) + Au (g/t) * 72.2. Assumptions include metal prices of $19.00 /oz Ag and $1,300 /oz Au; metallurgical recoveries of 83% for Ag and 87% for Au; and metal payability of 99.9% for Ag and 99.85% for Au.
4.             Numbers have been rounded as required by reporting guidelines. Totals may not sum due to rounding.

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Mineral Reserve Estimates

A silver equivalent (Ag-Eq) cut-off grade was estimated to complete San Martín’s initial mine design and initiate the process of underground mine optimization. This was developed using the following inputs: commodity price and exchange rate assumptions; current processing plant recoveries for silver and gold; current mining costs; processing, surface haulage, general and administration costs; and treatment and refining costs through current contracts with refining companies. A multiple-COG approach was used for stope optimization, as this allows the operation to benefit from the opportunity of extracting lower-grade material. Following completion of the mine designs and initial schedules, the various COGs were revised based on the detailed financial model. Even when the resulting mining costs estimates were lower than the initial estimates, the higher COGs were used in order to maintain profit margins. The COG was used as the main economic constraint and was derived from a Net Smelter Return (NSR) model prepared with the parameters described earlier; for this purpose, the silver and gold grades were expressed in terms of Ag-Eq. The Ag-Eq grade formula used was: Ag-Eq Grade = Ag Grade + Au Grade * [(Au Recovery * Au Payable * Au Price)] / (Ag Recovery * Ag Payable * Ag Price)

• Metal prices considered were $18.00 /oz Ag and $1,250 /oz Au.

• Metallurgical recovery used for oxide minerals was 84.3% for Ag, 92.8% for Au.

• Mineable zones were first determined by the initial COG and classification criteria. Stopes were then optimized based on selected mining methods and minimum stope widths.

• Dilution was assumed at 5% and mining recovery at 95% for both development and the areas mined using cut-and-fill methods.

Modifying factors for mining were applied on a stope-by-stope evaluation, and have been determined suitable for conversion to Mineral Reserves. To convert from Mineral Resources to Mineral Reserves, the resource blocks were interrogated by applying economic criteria as well as geometric constraints based on the mining method envisioned. Mineable blocks or stopes were defined by following this process.