Fatemeh Sahraei - Faculty of Management and Economics, Science and Research Branch, Islamic Azad University, Tehran, Iran
Jafar Jamali - Faculty of Management and Economics, Science and Research Branch, Islamic Azad University, Tehran, Iran
Hamid Reza Vakilifard - Department of Accounting, Faculty of Management and Economics, Science and Research Branch, Islamic Azad University, Tehran, Iran
Ali Zare - Department of Law, Faculty of Theology and Political Sciences, Sciences and Research Branch, Islamic Azad University, Tehran, Iran
Seyed Yaghoub Zeraatkish - Department of Agricultural Economic, Faculty of Agricultural Sciences and Food Engineering, Sciences and Research Branch, Islamic Azad University, Tehran, Iran

Companies should evaluate the nature of the crisis after a detailed pathology of the factors causing the problem and look for appropriate solutions to get out of this crisis. This study was conducted on ۱۴۴ companies from ۲۰۱۰-۲۰۲۱ to prioritize the factors affecting the exit from bankruptcy and financial revival of the companies using the analysis of multiplayer artificial neural networks. First, financial ratios obtained from the literature review and expert evaluation were independentist of each other through principal component analysis. Then, the main components affecting exit from bankruptcy under logistic regression models were identified, and finally, the final logistic model for exit from bankruptcy was presented. Based on the results, the essential financial variable in exiting bankruptcy is the change in capital increase policies from the place of stock issuance. The least critical variable is the change in dividend policies.

Bankruptcy, exit from bankruptcy, financial revival, Artificial Neural Network