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Financial Distress is the initial stage of bankruptcy. The ability to predict financial failure is an essential topic in financial research because it can be an early warning for companies before bankruptcy occurs. Various models have been developed to predict the occurrence of Financial Distress. The higher the accuracy of predictions, the more it will help the companys stakeholders to mitigate the impact of financial distress. This study aims to build Financial Distress models using the Artificial Intelligence Neural Network Model and the Discriminant Analysis Model; comparisons are then made evaluating the accuracy of the two models in predicting Financial Distress. The sample consisted of 35 non-financial companies that experienced forced delisting from the Indonesia Stock Exchange in the period 2010 - 2018. The results showed that the Artificial Intelligence Neural Network Model gave a better prediction than the Discriminant Analysis Model. It is crucial to consider the choice of predictor variables that determined the predictive success of the financial distress model.