Copula-Based Stochastic Frontier Models R package copulaSFM version 0.2.0 Provides estimation procedures for copula-based stochastic frontier models for cross-sectional data. The package implements maximum likelihood estimation of stochastic frontier models allowing flexible dependence structures between inefficiency and noise terms through various copula families (e.g., Gaussian and Student-t). It enables estimation of technical efficiency scores, log-likelihood values, and information criteria (AIC and BIC). The implemented framework builds upon stochastic frontier analysis introduced by Aigner, Lovell and Schmidt (1977) <doi:10.1016/0304-4076(77)90052-5> and the copula theory described in Joe (2014, ISBN:9781466583221). Empirical applications of copula-based stochastic frontier models can be found in Wiboonpongse et al. (2015) <doi:10.1016/j.ijar.2015.06.001> and Maneejuk et al. (2017, ISBN:9783319562176). Software Imports: stats, graphics, truncnorm, VineCopula, MASS Woraphon Yamaka <woraphon.econ@gmail.com> Comprehensive R Archive Network (CRAN) Woraphon Yamaka [aut, cre], Paravee Maneejuk [aut], Nuttaphong Kaewtathip [aut] GPL-3 2026-03-05 application/tgz https://CRAN.R-project.org/package=copulaSFM doi:10.32614/CRAN.package.copulaSFM