Abstract: The method of support vector regression (SVR) in combination with self organization feature mapping (SOFM) network was selected for grade interpolation in orebody, and was compared to the Thiessen polygons method, the distance power inverse ratio method and the Kriging method. The result shows that the prediction model of SVR is feasible and reliable for grade estimation.