Ensemble Explainable Machine Learning Models R package EEML version 0.1.1 We introduced a novel ensemble-based explainable machine learning model using Model Confidence Set (MCS) and two stage Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) algorithm. The model combined the predictive capabilities of different machine-learning models and integrates the interpretability of explainability methods. To develop the proposed algorithm, a two-stage Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) framework was employed. The package has been developed using the algorithm of Paul et al. (2023) <doi:10.1007/s40009-023-01218-x> and Yeasin and Paul (2024) <doi:10.1007/s11227-023-05542-3>. Software Imports: stats, MCS, WeightedEnsemble, topsis Dr. Ranjit Kumar Paul <ranjitstat@gmail.com> Comprehensive R Archive Network (CRAN) Dr. Md Yeasin [aut], Dr. Ranjit Kumar Paul [aut, cre], Dr. Dipanwita Haldar [aut] GPL-3 2024-08-01 application/tgz https://CRAN.R-project.org/package=EEML doi:10.32614/CRAN.package.EEML