Owing to the difficulty of traditional multi-variable regression methods to represent the surrounding rock deformation curve with inflexion points, a method for forecasting tunnel surrounding rock deformation using radial basis function neural networks is presented. This method not only can be utilized to approximate the complex deformation curves, but also has higher convergence speed and better globally-searching ability than those using BP neural networks. An example is given to show the effectiveness and practicability of this method.