In recent years, bankruptcy prediction has been a hot topic among the myriad of data analysts traversing across the globe so in this research paper I have presented a general framework regarding various methodologies for the prediction of bankruptcy by taking a skewed dataset and comparing it against the conventional methods. Also by taking into account various financial ratios of an enterprise and following a multi-variant approach of discriminant analysis, predicting the solvency of enterprise and thereby bankruptcy. In parallel to others, evolution in computing technology has given rise to an era in which Artificial Intelligence (AI) and machine learning form the foundation of bankruptcy prediction models. This paper aims at developing a framework of prediction using the ANN (Artificial Neural Network). The dataset will be used for analysis and the outcome of the study of conventional models will be viewed as a reference for comparison with the results of the current forecast model. Thus a breakthrough can be achieved in this sparsely trodden arena of finance which in the amalgamation of data science will alleviate the situations of banks and enterprises.