عنوان مقاله [English]
Financial distress and bankruptcy have a lot of cost that damage the economy of a country. Prediction of financial distress is a way that can help companies to prevent from occurring of financial distress.
In this study, we predict financial distress of manufacturing firms using artificial neural networks. Moreover, we present a comprehensive review of financial distress prediction models and artificial neural networks. The method of cross-validation is used to examine the effect of between sample variations in prediction. We use multiple discriminate analysis as comparative model. Based on a sample of 80 firms, our findings indicate that artificial neural networks are significantly better than multiple discriminate analyses in accuracy rate of prediction.