The topic of business failure is important because it can be used as a basis for policy making by stakeholders in a company or government. The results of business failure predictions can be used as company managers to take preventive measures for business failure. This study aim is to study the literature regarding the methods and results of predicting business failure from various sectors and regions. We used PRISMA (preferred reporting items for systematic reviews and meta-analyses) for conducting this research. As the result, we found twelve statistical methods for business failure prediction, including Hybrid Failure Prediction (HFP), Altman’s Z-score Model, Data Envelopment Analysis (DEA), Logistic Regression (LR), Neural Networks (NN), Support Vector Machine (SVM), Kernel Fuzzy C-Means (KFCM), IN01, IN05, Ohlson Model, Cart-Based Model and Cash-Flow-Based Measures. The highest result obtained by using cart-based model for dataset of financial indicators of Slovak companies with 92,00% accuracy.