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In this paper, we present the Py-CIU library, a generic Python tool for applying the Contextual Importance and Utility (CIU) explainable machine learning method. CIU uses concepts from decision theory to explain a machine learning model’s prediction specific to a given data point by investigating the importance and usefulness of individual features (or feature combinations) to a prediction. The explanations aim to be intelligible to machine learning experts as well as non-technical users. The library can be applied to any black-box model that outputs a prediction value for all classes