By default, the PDF- or Word-format diagnostic report contains essential goodness-of-fit plots. In addition, shrinkage and summary parameters tables can be also produced. Using simple syntax, the toolbox produces various goodness-of-fit diagnostics such as: - residual- and empirical Bayes estimate (EBE)-based plots, - distribution plots, - prediction- and simulation-based diagnostics (visual predictive checks). The package is currently compatible with Monolix versions 2016 and later, NONMEM version 7.2 and later and nlmixr. ggPMX enables straightforward generation of PDF, Word or PNG output files that contain all diagnostic plots for keeping track of modeling results. Intuitive functions and options allow for optimal figure customization and graphics stratification. The package builds on the R-package ggplot2 and aims at providing a workflow that is consistent, reproducible and efficient, resulting in high quality graphics ready-to-use in submission documents and publications. It generates standard diagnostic plots for mixed effect models used in pharmacometric activities. GgPMX is an open-source R package freely available on CRAN since April 2019. Authors: Amine Gassem, Irina Baltcheva, Christian Bartels, Thomas Dumortier, Seid Hamzic, Souvik Bhattacharya, Inga Ludwig, Ines Paule, Didier Renard, Bruno Bieth