Methods, such as part interpolation, whole interpolation, multiple\|linear regression and integrative model were used to interpolate the precipitation based on the annual mean precipitation from 120 climate stations in Hebei province and its adjacent areas (from 1971 to 2000). Results showed that numbers of interpolation climate stations, type of interpolation model and parameters of model influenced the interpolating precision. The smallest mean relative error (MRE) appeared in Spline or IDW models, followed by Kridging models, and bigger for the error of whole model Trend and Linear Regression Models. The integrative model, such as part model and linear regression model, could improve the interpolating precision and error distribution. In conclusion, integrative model is the suitable interpolating model for 80 and 40 climate stations in Hebei province, and IDW2 is best for 20 climate stations.