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The main objective of this study is to identify and predict detection financial fraud by using compliance and deviation degree of financial statements from Benford's law. In this regard, data of 98 companies listed on the Tehran Stock Exchange in the period 2006- 2015 (980 View), are studied. To achieve the research objectives, three hypotheses are considered and the linear multiple regression and logit model are used. The first hypothesis test results show that distribution of financial statement items follow Benford's Law. In other words, this law can be used to investigate irregularities. According to the results of the second hypothesis, top financial statements deviation from Benford's Law represents a financial fraud. The results of the third hypothesis indicates that deviation from Benford's Law in fraud detection year is reduced compared to previous years. In fact, managers inability in repeating the manipulation of digits in fraud detection year, reduces the financial statements deviation from Benford's law than what was in previous years.