This study predicted the bankruptcy companies listed in Japanese Stock Markets for the entire industry and individual industries using Multiple Discriminant Analysis (MDA), artificial neural networks (ANN) and support vector machines (SVMs), and compared the method which is the best method to predict the bankruptcy companies more precisely. The financial statements of the listed companies in the Tokyo Stock Exchange, the Osaka Securities Exchange, and other stock exchanges in Japanese stock markets were used as data. The data of 244 bankrupt companies that went bankrupt between 1991 and 2014 are used. On the other hand, data of 64708 non-bankrupt companies that did not go bankrupt between 1991 and 2014 for 24 years are used. The data is acquired from Nikkei NEEDS database. In MDA and ANN analysis, only for some industries bankruptcy prediction could be made accurately. On the other hand, SVM could predict bankruptcy in companies almost perfectly for each industry.