Two-axle rotary shaping is one of advanced sheet metal forming process that combined stamping ascendant used elastic medium with traditional rotary shaping principle. The prediction model of two-axle rotary shaping is set up to predict the springback for two-axle rotary shaping. It used the back propagation neural network because of the better nonlinear mapping ability. Some of data from the experiment and FEM simulation is applied to train the network; the other data is used to test the prediction result. The result showed that the value of prediction and experiment is in good agreement, and just small error is existed. It demonstrated that the neural network model might predict the springback of two-axle rotary shaping and reduce the number of simulation calculation and experiment operation. It can offer a powerful guidance for rapid choice of process parameters in production.