diff --git a/DESCRIPTION b/DESCRIPTION
index 2eef96b7..62ea0184 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,6 +1,6 @@
 Package: PLNmodels
 Title: Poisson Lognormal Models
-Version: 1.1.0
+Version: 1.1.1
 Authors@R: c(
   person("Julien", "Chiquet", role = c("aut", "cre"), email = "julien.chiquet@inrae.fr",
       comment = c(ORCID = "0000-0002-3629-3429")),
diff --git a/NEWS.md b/NEWS.md
index 0a0b6aed..5af5c3ff 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -1,3 +1,8 @@
+# PLNmodels 1.1.1 (2023-08-24)
+
+* Change behavior of `predict()` function for PLNfit model to (i) return fitted values if newdata is missing and (ii) perform one VE step to improve fit if responses are provided. 
+* Fix issue #114
+
 # PLNmodels 1.1.0 (2023-08-24)
 
 * Update documentation of PLN*_param() functions to include torch optimization parameters
diff --git a/man/PLNfit.Rd b/man/PLNfit.Rd
index 2703ac82..303c21cb 100644
--- a/man/PLNfit.Rd
+++ b/man/PLNfit.Rd
@@ -285,7 +285,13 @@ The list of parameters \code{config} controls the post-treatment processing, wit
 \subsection{Method \code{predict()}}{
 Predict position, scores or observations of new data.
 \subsection{Usage}{
-\if{html}{\out{<div class="r">}}\preformatted{PLNfit$predict(newdata, type = c("link", "response"), envir = parent.frame())}\if{html}{\out{</div>}}
+\if{html}{\out{<div class="r">}}\preformatted{PLNfit$predict(
+  newdata,
+  responses = NULL,
+  type = c("link", "response"),
+  level = 1,
+  envir = parent.frame()
+)}\if{html}{\out{</div>}}
 }
 
 \subsection{Arguments}{
@@ -293,12 +299,21 @@ Predict position, scores or observations of new data.
 \describe{
 \item{\code{newdata}}{A data frame in which to look for variables with which to predict. If omitted, the fitted values are used.}
 
+\item{\code{responses}}{Optional data frame containing the count of the observed variables (matching the names of the provided as data in the PLN function), assuming the interest in in testing the model.}
+
 \item{\code{type}}{Scale used for the prediction. Either \code{link} (default, predicted positions in the latent space) or \code{response} (predicted counts).}
 
+\item{\code{level}}{Optional integer value the level to be used in obtaining the predictions. Level zero corresponds to the population predictions (default if \code{responses} is not provided) while level one (default) corresponds to predictions after evaluating the variational parameters for the new data.}
+
 \item{\code{envir}}{Environment in which the prediction is evaluated}
 }
 \if{html}{\out{</div>}}
 }
+\subsection{Details}{
+Note that \code{level = 1} can only be used if responses are provided,
+as the variational parameters can't be estimated otherwise. In the absence of responses, \code{level} is ignored and the fitted values are returned
+}
+
 \subsection{Returns}{
 A matrix with predictions scores or counts.
 }
diff --git a/man/predict.PLNfit.Rd b/man/predict.PLNfit.Rd
index 8e7d177b..6bf64b77 100644
--- a/man/predict.PLNfit.Rd
+++ b/man/predict.PLNfit.Rd
@@ -4,13 +4,24 @@
 \alias{predict.PLNfit}
 \title{Predict counts of a new sample}
 \usage{
-\method{predict}{PLNfit}(object, newdata, type = c("link", "response"), ...)
+\method{predict}{PLNfit}(
+  object,
+  newdata,
+  responses = NULL,
+  level = 1,
+  type = c("link", "response"),
+  ...
+)
 }
 \arguments{
 \item{object}{an R6 object with class \code{\link{PLNfit}}}
 
 \item{newdata}{A data frame in which to look for variables and offsets with which to predict}
 
+\item{responses}{Optional data frame containing the count of the observed variables (matching the names of the provided as data in the PLN function), assuming the interest in in testing the model.}
+
+\item{level}{Optional integer value the level to be used in obtaining the predictions. Level zero corresponds to the population predictions (default if \code{responses} is not provided) while level one (default) corresponds to predictions after evaluating the variational parameters for the new data.}
+
 \item{type}{The type of prediction required. The default is on the scale of the linear predictors (i.e. log average count)}
 
 \item{...}{additional parameters for S3 compatibility. Not used}