A discretization model called ROGAND ( ROugh sets, Genetic Algorithm and Neural network based Discretization ) is presented in the paper, which combines Rough set theory with the genetic algorithm to build a four-layer neural network. This model consists of the data preprocessor (DP), the discretization module(DM) and the optimization module (OM). The discretized intervals obtained through the ROGAND model is independent on the candidates of cut-point sets and the denoted values can be more precise. The experiments indicate that the method is effective and the output cut-points are accurate and easy-set.