Good performance of intelligent models has increased their use in predicting different hydrological phenomena.so it is necessary to evaluate the performance of models developed in different regions of the world with different climatic, hydrological and physiographic features in order to comment on their performance in different regions.Hence, to predict the flood discharge of the basin, the data of the region have been collected for a period of 10 years with the length of the statistical period (2010-2020) using the intelligent model of gene expression planning.After analyzing the model's evaluation criteria, the results showed the good and high performance of the model in predicting flood discharge.Using both synthetic hydrograph Gary and Gamma models, the significant runoff parameters (flood peak discharge error), (Time to reach flood peak discharge error), and (flow volume error) and three criteria (Root mean square error, mean absolute error and determination of coefficient ) were evaluated to determine the shape of the flood hydrograph. Also, using the scoring and ranking method for each of the errors and the best model in estimating each of the flood characteristics was determined. based on the results, the values of the expressed domains for the gamma model are (9.50, -12.9), (20.09, -40.1), (75, -100), (0.42, 1.66), (3.20, 1.03) and (0.94, 0.87) The results showed the superiority of the gamma model Gary model and the selected model was able to appropriately estimate the characteristics of the flood hydrograph. It is also recommended to study this model in flood modeling in other ungauged watershed