Abstract: Financial distress and bankruptcy result in a lot of costs. The costs will extend to different groups such as creditors, investors, managers, legal institutions and eventually capital owners. Bankruptcy prediction is a way that significantly can avoid financial distress. The purpose of the study is to design a system using artificial neural network to predict bankruptcy of companies listed in Tehran Stock Exchange before occurring bankruptcy, this system should be designed in a way that can predict the financial situation of company within the next three years. The research method is ex-post facto or survey and the statistical population of research including companies listed in Tehran Stock Exchange during 2001-2010. The data of 54 companies (30 bankrupt companies and 24 companies with Tobin Q above one) was tested by two parameters: 0.15 and 03% accuracy (optimism and pessimism).