diff --git a/NAMESPACE b/NAMESPACE
index 96c2932..b81e082 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -212,6 +212,8 @@ importFrom(lme4,lmer)
 importFrom(methods,setMethod)
 importFrom(outliers,grubbs.test)
 importFrom(outliers,outlier)
+importFrom(pROC,ci.se)
+importFrom(pROC,roc)
 importFrom(parallel,clusterApply)
 importFrom(parallel,clusterEvalQ)
 importFrom(parallel,clusterExport)
diff --git a/R/plotAUC.R b/R/plotAUC.R
index 758bc86..376b4e3 100644
--- a/R/plotAUC.R
+++ b/R/plotAUC.R
@@ -4,19 +4,52 @@
 #'
 #' @param modelingResult output from either
 #'          \code{lr_modeling} or \code{rf_modeling}
+#' @param CI (logical) Plot confidence interval or not. Default is False.
+#' @param ... further arguments passes to the \code{plot} method of the
+#'             \code{\link[pROC]{ci.se}} object of the \code{pROC} package.
+#'
 #'
 #' @importFrom ROCR performance
 #' @importFrom graphics abline
+#' @importFrom pROC roc ci.se
 #'
 #' @export plotAUC
 #'
-plotAUC <- function(modelingResult){
-    perf <- performance(modelingResult$pred,"tpr","fpr")
-    # x=1-spec, y=sens
-    plot(perf,
-         main=sprintf("AUC: %s", round(modelingResult$auc,2)),
-         col=2, lwd=2)
-    abline(a=0,b=1,lwd=2,lty=2,col="gray")
+plotAUC <- function(modelingResult, CI = FALSE, ...){
+
+   if(!CI){
+      perf <- performance(modelingResult$pred,"tpr","fpr")
+       # x=1-spec, y=sens
+       plot(perf,
+            main=sprintf("AUC: %s", round(modelingResult$auc,2)),
+            col=2, lwd=2)
+       abline(a=0,b=1,lwd=2,lty=2,col="gray")
+   }else{
+      old_par <- par()
+      par(pty="s")
+      pROC_obj <- roc(modelingResult$pred@labels[[1]],
+                      modelingResult$pred@predictions[[1]],
+                      direction = "<",
+                      smoothed = T,
+                      # arguments for ci
+                      ci=TRUE,
+                      ci.alpha=0.95,
+                      stratified=FALSE,
+                      # arguments for plot
+                      plot=TRUE,
+                      auc.polygon=F,
+                      max.auc.polygon=F,
+                      grid=F,
+                      print.auc=TRUE,
+                      print.auc.y=0.1,
+                      print.auc.x=0.8,
+                      show.thres=TRUE)
+      sens.ci <- ci.se(pROC_obj)
+      plot(sens.ci, type="shape", col="#FF8888", conf=95, ...)
+      abline(a=1,b=-1,lty=2,lwd=2,col="grey50")
+      par(old_par)
+   }
+
 }
 
 
diff --git a/man/plotAUC.Rd b/man/plotAUC.Rd
index 99de527..7fb0795 100644
--- a/man/plotAUC.Rd
+++ b/man/plotAUC.Rd
@@ -4,11 +4,16 @@
 \alias{plotAUC}
 \title{Plot AUC}
 \usage{
-plotAUC(modelingResult)
+plotAUC(modelingResult, CI = FALSE, ...)
 }
 \arguments{
 \item{modelingResult}{output from either
 \code{lr_modeling} or \code{rf_modeling}}
+
+\item{CI}{(logical) Plot confidence interval or not. Default is False.}
+
+\item{...}{further arguments passes to the \code{plot} method of the
+\code{\link[pROC]{ci.se}} object of the \code{pROC} package.}
 }
 \description{
 Plot AUC after LOOCV Model Evaluation