Abstract: Soil samples were collected in Jincang Forest Farm, Wangqing Forestry Bureau to study spatial distribution of soil organic carbon (SOC) and nutrients. Geostatistics was used to predict their spatial distribution in the study area, and the prediction results were interpolated using regressionkriging and ordinary kriging. Multiple linear regression was used to study the relationship between SOC and spatial factors. The results showed the SOC density (SOCD) at 0-60 cm was (16.14±4.58) kg·m^-2. Soil organic carbon decreased significantly with the soil depth. With the increasing soil depth, total N, total P, total K, available P and readily available K concentrations decreased. Stepwise regression analysis showed that SOC had good correlation with elevation and cosine of aspect, with the determination coefficient of 0.34 and 0.39, respectively (P<0.01). Soil organic carbon at 0-20 cm and 0-60 cm soil layers conformed to Gaussian model and exponential model. Compared with ordinary kriging, the prediction accuracy was improved by 18%-58% using regressionkriging. Regressionkriging interpolation was also applied to study spatial heterogeneity of soil total N.