diff --git a/ChangeLog b/ChangeLog
index 26d0fb4..0321ded 100644
--- a/ChangeLog
+++ b/ChangeLog
@@ -1,8 +1,9 @@
-2017-04-05
+2017-04-06
 
         * Version 1.3.0 released
         ========================
 
+        Use correct ROOT histograms in csroot2caldb
         Implement regression scheme in cssens and remove num_avg parameter (#1989)
         Copy cscripts into bin directory instead of creating a symbolic links (#1987)
         If code originates from Git, always compile the Python bindings (#1985)
diff --git a/NEWS b/NEWS
index 649abee..ee050fe 100644
--- a/NEWS
+++ b/NEWS
@@ -1,6 +1,6 @@
 New Features and Important Changes in ctools 1.3.0.dev1
 
-5 April 2017
+6 April 2017
 
 
 Introduction
@@ -137,6 +137,11 @@ A regression scheme now replaces the averaging scheme in cssens as this
 allows more accurately the prediction of the flux value at the threshold
 Test Statistic. The num_avg parameter has been removed (#1989).
 
+The names of some ROOT histograms has been changed in the Monte Carlo data
+and the "EffectiveAreaEtrue_offaxis" needed to be changed to
+"EffectiveAreaEtrueNoTheta2cut_offaxis" and "EffectiveAreaEtrue" to
+"EffectiveAreaEtrueNoTheta2cut" in csroot2caldb.
+
 
 Examples
 --------
diff --git a/cscripts/csroot2caldb.py b/cscripts/csroot2caldb.py
index 1a36e74..b89d770 100755
--- a/cscripts/csroot2caldb.py
+++ b/cscripts/csroot2caldb.py
@@ -551,13 +551,13 @@ class csroot2caldb(ctools.cscript):
         self._log_header1(gammalib.TERSE, 'Generate effective area extension')
 
         # Get relevant ROOT histograms
-        etrue = tfile.Get('EffectiveAreaEtrue_offaxis')
+        etrue = tfile.Get('EffectiveAreaEtrueNoTheta2cut_offaxis')
 
         # If requested then normalize the 2D histogram on the on-axis 1D
         # histogram. This assures that the 2D histogram has the same on-axis
         # effective area dependence as the 1D histogram.
         if self['norm1d'].boolean():
-            etrue_1D = tfile.Get('EffectiveAreaEtrue')
+            etrue_1D = tfile.Get('EffectiveAreaEtrueNoTheta2cut')
             self._renorm_onaxis(etrue, etrue_1D)
 
         # If requested then rebin the effective area Etrue histogram. This