Bayesian Estimation of Adsorption Isotherms via MCMC R package adsoRptionMCMC version 0.1.0 Provides tools for Bayesian parameter estimation of adsorption isotherm models using Markov Chain Monte Carlo (MCMC) methods. This package enables users to fit non-linear and linear adsorption isotherm models—Freundlich, Langmuir, and Temkin—within a probabilistic framework, capturing uncertainty and parameter correlations. It provides posterior summaries, 95% credible intervals, convergence diagnostics (Gelman-Rubin), and visualizations through trace and density plots. With this R package, researchers can rigorously analyze adsorption behavior in environmental and chemical systems using robust Bayesian inference. For more details, see Gilks et al. (1995) <doi:10.1201/b14835>, and Gamerman & Lopes (2006) <doi:10.1201/9781482296426>. Software Imports: MCMCpack, coda, stats, graphics Suggests: testthat Paul Angelo C. Manlapaz <pacmanlapaz@gmail.com> Comprehensive R Archive Network (CRAN) Paul Angelo C. Manlapaz [aut, cre] (ORCID: <https://orcid.org/0000-0002-1203-2064>) GPL-3 2025-05-30 application/tgz https://CRAN.R-project.org/package=adsoRptionMCMC doi:10.32614/CRAN.package.adsoRptionMCMC