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Response surface methodology (RSM) and artificial neural network (ANN) have been used to develop predictive models for simulation and optimization of reverse osmosis (RO) desalination process. Sodium chloride aqueous solutions were employed as model solutions for a RO pilot plant applying polyamide thin film composite membrane, in spiral wound configuration. The input variables were sodium chloride concentration in feed solution, C, feed temperature, T, feed flow-rate, Q, and operating hydrostatic pressure, P. The RO performance index, which is defined as the salt rejection factor times the permeate flux, has been considered as response. Both RSM and ANN models have been developed based on experimental designs. Two empirical polynomial RSM models valid for different ranges of feed salt concentrations were performed. In contrast, the developed ANN model was valid over the whole range of …