NGBoost implements Natural Gradient Boosting for probabilistic prediction, outputting full probability distributions rather than point estimates. It is built on scikit-learn with modular support for different proper scoring rules, distributions, and base learners. The library enables uncertainty quantification in regression and classification tasks through its natural gradient descent approach.