Abstract: A method is provided for debiasing machine learning models. The method includes obtaining (i) an initial model that is a trained and tree-based machine learning model and (ii) a minimum acceptable threshold accuracy, for (iii) one or more protected classes. The initial model demonstrates adverse impact on one or more protected classes. The method includes identifying branches of the initial model to prune, based on the branches' impact on one or more protected classes. The method includes applying a pruning algorithm to prune the branches of the initial model to generate one or more forest models, such that (i) predictive accuracy of the one or more forest models is above the minimum threshold accuracy, and (ii) the one or more forest models are less discriminatory than the initial mode.