diff --git a/doc/jvm/xgboost4j_spark_tutorial.rst b/doc/jvm/xgboost4j_spark_tutorial.rst
index dbfc6d765..c8fd951ed 100644
--- a/doc/jvm/xgboost4j_spark_tutorial.rst
+++ b/doc/jvm/xgboost4j_spark_tutorial.rst
@@ -345,6 +345,16 @@ and then loading the model in another session:
   val xgbClassificationModel2 = XGBoostClassificationModel.load(xgbClassificationModelPath)
   xgbClassificationModel2.transform(xgbInput)
 
+.. note::
+
+  Besides dumping the model to raw format, users are able to dump the model to be json or ubj format from ``version 2.0.0+``.
+
+  .. code-block:: scala
+
+    val xgbClassificationModelPath = "/tmp/xgbClassificationModel"
+    xgbClassificationModel.write.overwrite().option("format", "json").save(xgbClassificationModelPath)
+
+
 With regards to ML pipeline save and load, please refer the next section.
 
 Interact with Other Bindings of XGBoost
diff --git a/doc/tutorials/saving_model.rst b/doc/tutorials/saving_model.rst
index 87e54054c..3ec329968 100644
--- a/doc/tutorials/saving_model.rst
+++ b/doc/tutorials/saving_model.rst
@@ -44,6 +44,7 @@ with normal model IO operation. Currently, memory snapshot is used in the follow
 * Python package: when the ``Booster`` object is pickled with the built-in ``pickle`` module.
 * R package: when the ``xgb.Booster`` object is persisted with the built-in functions ``saveRDS``
   or ``save``.
+* JVM packages: when the ``Booster`` object is serialized with the built-in functions ``saveModel``.
 
 Other language bindings are still working in progress.
 
@@ -68,6 +69,12 @@ a filename with ``.json`` or ``.ubj`` as file extension, the latter is the exten
 
   xgb.save(bst, 'model_file_name.json')
 
+.. code-block:: Scala
+  :caption: Scala
+
+  val format = "json"  // or val format = "ubj"
+  model.write.option("format", format).save("model_directory_path")
+
 .. note::
 
   Only load models from JSON files that were produced by XGBoost. Attempting to load