Identification of discrete–time non–linear stochastic systems which can be represented by a rational input–output model is considered. A prediction–error parameter estimation algorithm is developed and a criterion is derived using results from the theory of hypothesis testing to determine the correct model structure. The identification of a simulated system, and a heat exchanger are included to illustrate the algorithms.