Probabilistic Regression Trees R package PRTree version 1.1.0 Implementation of Probabilistic Regression Trees (PRTree), providing functions for model fitting and prediction, with specific adaptations to handle missing values. The main computations are implemented in 'Fortran' for high efficiency. The package is based on the PRTree methodology described in Alkhoury et al. (2020), "Smooth and Consistent Probabilistic Regression Trees" <https://proceedings.neurips.cc/paper_files/paper/2020/file/8289889263db4a40463e3f358bb7c7a1-Paper.pdf>. Details on the treatment of missing data and implementation aspects are presented in Prass, T.S.; Neimaier, A.S.; Pumi, G. (2025), "Handling Missing Data in Probabilistic Regression Trees: Methods and Implementation in R" <doi:10.48550/arXiv.2510.03634>. Software Depends: R (>= 4.3.0) Imports: tidyr (>= 1.3.0), gridExtra (>= 2.3), stats, grDevices, utils, tidyselect, graphics, rlang Suggests: ggplot2 Taiane Schaedler Prass <taianeprass@gmail.com> Comprehensive R Archive Network (CRAN) Taiane Schaedler Prass [aut, ths, cre] (ORCID: <https://orcid.org/0000-0003-3136-909X>), Alisson Silva Neimaier [aut] (ORCID: <https://orcid.org/0000-0002-7524-0776>) GPL (>= 3) 2026-07-13 application/tgz https://CRAN.R-project.org/package=PRTree doi:10.32614/CRAN.package.PRTree