The AI Explainability 360 toolkit, an LF AI Foundation incubation project, is an open-source library that supports the interpretability and explainability of datasets and machine learning models. The AI Explainability 360 Python package includes a comprehensive set of algorithms that cover different dimensions of explanations along with proxy explainability metrics. There is no single approach to explainability that works best. The toolkit is designed to translate algorithmic research from the lab into the actual practice of domains as wide-ranging as finance, human capital management, healthcare, and education.