In the construction process of excavating machinery, different mining states directly affect the mobile arm hinge point bearing force size. Aimed at the problem of hydraulic excavator mobile arm hinge point fracture occurs frequently, a method study based on Support Vector Machine (SVM) was proposed. Based on SVM, the maximum hinge point bearing force of mobile arm was found out by using ADAMS simulation, the primary features of vector influencing the hinge point force were determined and the bearing force prediction model of mobile arm hinge point was built based on SVM. The SVM model was validated by using MATLAB tool, the example was verified of the feasibility of the SVM prediction mobile arm hinge point bearing force, and as compared with the BP neural network which was more accurate in small samples. A basis support is provided in selecting working parameters of mobile arm.