Based on artificial immune clustering and Immune Evolutionary Algorithm (IEA), a novel hybrid RBF design method is proposed. The artificial immune clustering is used to adaptively specify the amount and initial position of centers of basis functions in RBF network according to input data set. Then immune evolutionary algorithm is used to train the RBF network, which reduces the searching space of canonical evolutionary algorithm and improves the convergence speed. Computer simulations demonstrate that the RBF network designed in this method has a concise structure with good generalization ability.