Based on the prediction methods of regression model, times series model, as well as the commonly used prediction methods of grey model and BP neural network, RBF neural network model was established in this case to analysis and predict the national railway freight volume in detail. The original data of railway freight volume was used to construct times series, analyze and deal with the times series. The processed data were constructed as a nonlinear mapping. RBF neural network was used to approach it. The grey model, BP neural network model and RBF neural network model were simulated by using Matlab. It was concluded that average relative errors of the three kinds of prediction model were 7.67%, 4.79% and 1.31% respectively. The results showed that the prediction method based on RBF neural network was better than other, could provide support for railway freight volume forecasting.