Abstract: This paper mainly studies the influence of different types of spatial interpolation methods on the prediction accuracy of soil organic matter,and selects the best evaluation method through comparative analysis.This paper selects the data of 386 soil organic matter samples in a Study area in Jiaodong hilly area of Eastern Liaoning Province,and displays them in ArcMap10.2.2 with the support of the platform and IBMSPS Statistics 25 software,the sample data are statistically analyzed,and different types of interpolation methods are used to predict the value of soil organic matter in the study area.The prediction errors of cross validation of different interpolation methods are compared,and the most appropriate method is selected.In ArcGIS 10.2.2 in the platform,it is proved that the fitting degree of the data after box cox conversion is the highest by means of spatial exploration and analysis of QQ chart.The prediction results of cross validation from different interpolation methods show that the root mean square error of the global polynomial interpolation method is the smallest and the spatial interpolation effect is the best.