GPBoost is a machine learning library enabling both independent use and combination of tree-boosting, Gaussian processes, and mixed-effects models (latent Gaussian variable models). It is implemented predominantly in C++ with C interface, and exposes Python and R packages for integration. The library implements the GPBoost algorithm documented in Sigrist (2022, JMLR).