forecasting the profitability in the firms listed in tehran stock exchange using data envelopment analysis and artificial neural network

profitability as the most important factor in decision-making, has always been considered by stake­holders in the company's profitability. also can be a basis for evaluating the performance of the managers. the ability to predict the profitability can be very useful to help decision-makers. that's why one of the most important issues is the expected profitability. the importance of these forecasts depends on the amount of misalignment with reality. the amount of deviation is less than the forecast of higher accuracy. although there are various methods for predicting but the use of artificial intelligence techniques is increasing due to fewer restriction. the aim of this study is to evaluate the predictive power of profitability using dea and neutral network, to enhance the decision-making users of 2012 to 2015of 7 premier financial ratios were used as independent variables. test results show that both of ann and dea have ability to forecast profitability and given that neutral network prediction accuracy is higher than the dea, the model predict better the profitability of companies.