Owners, managers, investors, creditors, trade companies and state organization are interested in evaluating the financial position of the companies, because they will be imposed many expenses if bankruptcy is occurred. Now a days various patters are used including statistical technique (discriminate analysis, logistic, analysis factors) and artificial intelligent techniques (neural networks (NN), decision trees, case based reasoning, genetic algorithm, rough sets, support vector machine, fuzzy logic) and the combination of these two technique for predicating this bankruptcy.The goal of this study is to determine patterns using the financial variables (financial ratio of the profit & loss account and balance sheet) to increase the ability of decision making for financial statement users to predicate the financial distress.In this study (article) patterns to predicate financial distress (patterns based on traditional methods (MDA), linear genetic algorithm, nonlinear genetic algorithm and neural networks have been compiled to predicate financial distress two years before their occurrence. then respecting obtained results the patter based neural network has the highest ability to predicate the financial distress of the companies.