In order to ensure the grinding quality of the multi-head screw rotor belt grinding quality and improve the grinding efficiency at the same time. The multi-head screw rotor was ground by using a double abrasive belt grinding device, an orthogonal test was designed, and the WOA-RBF prediction model was established by using the orthogonal test database to judge the accuracy of the prediction model by the coefficient of determination R2, root mean square error (RMSE) and mean absolute error (MAE), and the results were better than the comparison models. The output surface roughness and material removal rate values of the WOA-RBF prediction model were used as the objective functions of the dual-objective optimization model, and a dual-objective optimization model based on the Multi-objective exponential distribution optimizer (MOEDO) was established. The model is solved to obtain the Pareto optimal solution set, and the optimized process parameter values, surface roughness and material removal rate values are obtained through the evaluation function. The surface roughness and material removal rate of the grinding screw rotor after grinding were 0.462 μm and 7.78 mm3/s, respectively, and the errors between the test results and the dual-objective optimization results were within a reasonable error, which verified the accuracy of the model. The results of the dual-objective optimization were compared with the results of the best set of orthogonal tests, and the surface roughness increased by 37.5%, but still met the technical requirements of the workpiece, while the material removal rate increased by 84.23%.The results show that the proposed dual-objective optimization model can improve the grinding efficiency while ensuring the surface quality, and can also provide a reference for the decision-making optimization of surface quality and material removal rate in other processing processes.