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This study develops a bankruptcy prediction framework using hybrid resampling, stacking ensembles, and explainable AI to enhance minority-class detection in imbalanced financial data. The results highlight GRU with SMOTE-ENN as the best performer and SHAP analysis for identifying key bankruptcy risk predictors.