​Predicting business insolvency is considered one of the main supportive sources of information for decision making by financial institutions, investors, creditor, and other participants in the business. The financial reporting system provide relevant information that could be used to assess the financial position of the firms to help users making right decision about the firm. It is become crucial to have an early prediction model that provide accurate assurance for users about the health situation of the business. Recent studies focused on using data mining tools instead of traditional statistical methods for developing models to classify firm into healthy or failed according to information from its financial ratios extracted from their financial reports. In this study, we develop insolvency perdition models based on three modelling techniques, named, logistic regression (LR), (as a statistical widely used method) and artificial neural network (ANN) and support vector machine (SVM) (as a data mining modelling tools). Results of the study revealed the outperformance of SVM in predicting financial insolvency based on performance measurements.