Variable Selection in High-Dimensional Logistic Regression Models using a Whitening Approach R package WLogit version 2.1 It proposes a novel variable selection approach in classification problem that takes into account the correlations that may exist between the predictors of the design matrix in a high-dimensional logistic model. Our approach consists in rewriting the initial high-dimensional logistic model to remove the correlation between the predictors and in applying the generalized Lasso criterion. Software Depends: R (>= 3.5.0) Imports: cvCovEst, genlasso, tibble, MASS, ggplot2, Matrix, glmnet, corpcor Suggests: knitr Wencan Zhu <wencan.zhu@yahoo.com> Comprehensive R Archive Network (CRAN) Wencan Zhu GPL-2 2023-07-17 application/tgz https://CRAN.R-project.org/package=WLogit doi:10.32614/CRAN.package.WLogit