Amorphophallus rivieri (the corpse flower) is a traditional edible and medicinal plant in China. This species is distributed in the south part of the Qinling Mountains, China. We assimilated data about A. rivieri cultivation, environmental information from 28 sampling sites in the Qinling Mountains, climate data from 45 weather stations in the Qinling Mountains from 1961 to 2010, soil data with 1 km × 1 km spatial resolution and DEM data with 30 m × 30 m spatial resolution in the Qinling Mountains, A. rivieri data collected throughout China, and a specific report on A. rivieri in Shaanxi Province. We obtained 20 assessment factors that were significantly correlated when evaluating A. rivieri yield against environmental factors. The key environmental factors affecting the distribution of A. rivieri cultivation included 13 dominant climate factors, 4 dominant soil factors, and 3 dominant topographical factors. These dominant factors were 1) Frost-free duration (D), 2) Annual average temperature (T_n), 3) Annual total active temperature(≥10°C)(T_≥10djw), 4) Monthly mean maximum temperature from July to August (T_78zg), 5) Annual precipitation (P_n), 6) Monthly mean daily temperature range from July to September (T_79gc), 7) Monthly mean temperature from May to October (T_510p), 8) Monthly mean temperature from July to August (T_78p), 9) Monthly mean relative air humidity from July to August (Q₇₈), 10) June precipitation (P₆), 11) July precipitation (P₇), 12) August precipitation (P₈),13) September precipitation (P₉), 14) Topsoil depth (H), 15) Topsoil pH(H₂O)(pH), 16) topsoil texture classification (C), 17) Topsoil organic matter (O), 18) Aspect (A), 19) Slope (S), 20) Altitude elevation (h). Using Geographic Information System (GIS) and a multivariate regression model, the climate factors were rasterized. Then, we used fuzzy mathematics analysis, analytic hierarchy process (AHP), and the weighted means method to set up the subjection function and determine the weight of each factor. We set up a model of ecological suitability for A. rivieri in the Qinling Mountains of Shaanxi Province, and determined the spatial distribution of suitable planting areas for this species. The root-mean-square error (RMSE) was used to evaluate the accuracy of the model predictions. The RMSE value reached 7.8%, which indicated that the predictive accuracy of the model was "Excellent." The results showed that the ecological planting suitability model identified a relationship between potential A. rivieri cultivation distribution and the environmental factors. Highly suitable, moderately suitable, marginally suitable, and unsuitable planting areas of 1 214.42 km², 2 015.60 km², and 3 115.03 km², and 5 580.02km² were identified for A. rivieri, respectively. The potential suitable planting areas for A. rivieri were mainly distributed in the south central part of Hanzhong district, the south central part of Ankang district, and the southeast part of Shanluo district. This information on the potential suitable planting area of A. rivieri is valuable for providing baseline data, scientific information, and a research platform for understanding the ecology, geography, and environmental science of this important medicinal species.