【Objective】 The site form index of three common tree species birch, poplar and Picea crassifolia in the Huangshui Large-scale Forest Farm in Qinghai Province was used to analyze the landform, aspect, slope, soil type, soil thickness, and annual average temperature, annual rainfall, annual solar radiation, and other factors of the growing area. The site quality evaluation of large-scale forest farms was carried out, and a comprehensive database of forestland quality evaluation was constructed to achieve the goal of guiding the scientific afforestation and management of forest farms and maximizing the value of forest land productivity and ecological services. 【Method】 First, according to the type of inventory data within the modeling area, the advantage of each plot was obtained, and the site form index of the plot was obtained. Following this, to analyze its relationship with landform, aspect, slope, soil type, soil thickness, annual average temperature, annual rainfall, annual solar radiation, and other factors, the factor analysis was used to select the dominant factors affecting the topographic index, and a regression model was established. According to the calculated average of the site form index of the three common tree species, the cluster analysis was carried out, and the forest land was divided into five grades: Ⅰ, Ⅱ, Ⅲ, Ⅳ and Ⅴ, and the forest land quality distribution map was prepared. Finally, according to the classification, the results were verified, and corresponding management measures were proposed. 【Result】 Grade Ⅰ forest land area was 3 409.37 hm ², accounting for 1.39% of the total forest land area; Grade Ⅱ forest land area was 38 765.07 hm ², accounting for 15.77%; Grade Ⅲ forest land area was 78 989.17 hm ², accounting for 32.14%; Grade Ⅳ forest land area was 77 102.74 hm ², accounting for 31.38%; and Grade Ⅴ forest land area was 47 477.50 hm ², accounting for 19.32%. Based on the overall classification results, the forest land quality grade of large-scale forest farms was low, mainly Ⅲ and Ⅳ forest land. The corrected rate of on-site verification quality grade was 88%, and the corrected rate was high. 【Conclusion】 It is feasible to obtain high advantages through the standard wood, sample wood bank, and sample base bank in the first type of inventory data. Following this, the topographic factors, soil factors, and meteorological factors can be selected as the evaluation factors. The introduction of multiple factors makes the evaluation results more objective and improves the accuracy of the evaluation. Using multi-tree species site form indexes for a comprehensive evaluation, especially the evaluation of site quality of non-forest land is a more effective method.