Assessing the quality of forest sites is crucial for evaluating the potential productivity of forests and formulating effective management strategies. Therefore, it is essential to understand how environmental variables affect the site quality. This study focuses on quantifying the effects of 44 different environmental variables including climate, topography, and soil properties on the site index of Larix kaempferi plantations in three different climate regions in China, utilizing the random forest algorithm. L. kaempferi site index was determined from stem analysis data by felling dominant trees from 51 even-aged stands. The results indicated that the proposed random forest model explained ~59.47% of site index variations. Among many environmental variables, available phosphorus, pH, degree-days above 5°C (DD5), and spring mean maximum temperature (Tmax_MAM) had significant effects on the site index (P < 0.05), and the importance of soil chemical properties generally exhibits relatively larger effects on the site index than climate variables and topography variables. The partial dependence analysis revealed that the L. kaempferi plantations had maximum values at ~30 mg/kg of available phosphorus in the first soil layers, 30 mg/kg of available phosphorus in the second soil layers, 20 mg/kg of available phosphorus in the third soil layers, the DD5 between 2,600and 3,000°C, and Tmax_MAM ~15°C. Our findings attempt to provide a better understanding of the site–growth relationship.