The increased number of restatements in recent years has increased the wor-ries about the quality of Financial reporting among the beneficiary groups. The pres-ence of prior period adjustments and, subsequently, the Financial restatements have a negative impact on the relatedness and reliability of the Financial state-ments. The present study is aimed to present an appropriate criterion for predict-ing the Financial restatements based on the Beneish model and its indices in companies admitted to the Tehran Stock & Exchange between 2009 and 2020. For this purpose, a total of 265 companies were selected considering the limitations. Also, the model estimation was per-formed using Beneish's primary model, a meta-heuristic neural network model, and optimization through genetic programming. As indicated by the obtained results based on the confusion matrix, the efficiency of the pro-posed model derived from the enhanced Beneish model with a genetic algo-rithm(S – 𝑆𝑐𝑜𝑟𝑒) had a total prediction accuracy of 73.21%, which was the highest prediction power compared to the Beneish Model .