ﻧﺨﺴﺘﯿﻦ ﻫﻤﺎﯾﺶ ﻣﻠﯽ ﻋﻠﻮم ﻣﺪﯾﺮﯾﺖ ﻧﻮﯾﻦISSN:2322-1151 اﺳﺘﺎن ﮔﻠﺴﺘﺎن, ﮔﺮﮔﺎن- ﭘﻨﺠﻢ ﺷﻬﺮﯾﻮر1391 The Conference on Modern Management Sciences 1 The classification of Iranian banks based on Artificial Neural Network (ANN) Mahdi Salehi (corresponding author) Faculty of Economics and Administrative Sciences, Ferdowsi University of Mashhad, Iran, E-mail:Mahdi_salehi54@yahoo.com Elahe Torabi Department of Accounting, Science and Research Branch, Islamic Azad University, Nyshabour, Iran. Jalil Khaksar Department of Accounting, Mashhad Branch, Islamic Azad University, Mashhad, Iran. Abstract In this study, it is attempted to examine the banking practice in Iran based on new scientific methods. It is used the financial ratios demonstrating healthy or non-healthy of banks to assess the financial health of listed banks in Tehran Stock Exchange. The assessment of these ratios with use of Neural Network (NN) as a non-parametric method for modeling is recommended for presenting this model. Information about the financial health of banks could be effective on the decisions of different groups of banks’ financial reports users, including shareholders, auditors, stock exchange, central bank and etc. Keywords: Neural Network(NN), Artificial Neural Network(ANN), Multi-Layer Perceptron (MLP), classification Introduction The role of banks in providing services to governments and society is not only undeniable but also was very significant and crucial and can be examined from different point view. Managing the peoples’ life affairs and countries’ economic affairs requires banks. It is possible to have a good influence on the decisions of users according to the importance of banks in modern societies with classifying the banks based on their financial health. According to this of banks in society is as the same as blood in vessel, there for it seems impossible to live without banks. On the other hand ,Neural Network (NN) has emerged over the years and has made remarkable contribution to the advancement of various fields of endeavor. The NN has been ray effective in the field of engineering, agriculture, economy, financial issues. Based on this efficiency we attempts to examine the financial health of banks based on 10 significant and crucial variables in NN.