Abstract: In this study, several radial basis function networks are compared according to their approximation ability in time series forecasting problems. Optimal values for the tested parameters are obtained using computer simulation runs. Effects of width selection in Gaussian Kernels, of the number of neurons in the hidden layer, and of selection of kernel function are investigated.