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Predicting rivers flow, as one of the main resources of water for human beings, has always been one of the important issues discussed in hydrology and water resources. So, different models have been used for modeling and predicting rivers flow.
 In this study, two genetic models, Gene Expression Programming (GEP) and genetic programming (GP) were evaluated. Flow, temperature, precipitation, and evaporation data were used to model the daily flow in Tale Zang station. The results showed that GEP model, with R2=0.86 and RMSE=0.0030 m3/s, had the better performance than GP model, with R2=0.85 and RMSE=0.0037 m3/s. Moreover, the speed of GEP was more than GP and had ability to present results in a short time. By increasing the number of data, the speed of GP decreased and sometimes it couldn’t present results, while GEP had the ability to work with more data and model the river flow.