diff --git a/python/pyspark/ml/base.py b/python/pyspark/ml/base.py
index a7a58e17a43e..d502bb181959 100644
--- a/python/pyspark/ml/base.py
+++ b/python/pyspark/ml/base.py
@@ -116,3 +116,17 @@ class Model(Transformer):
     """
 
     __metaclass__ = ABCMeta
+
+
+class HasNumFeaturesModel:
+    """
+    Provides getter of the number of features especially for model class
+    It should be mixin with JavaModel.
+    """
+    @property
+    @since("1.7.0")
+    def numFeatures(self):
+        """
+        The number of features used to train the model.
+        """
+        return self._call_java("numFeatures")
diff --git a/python/pyspark/ml/classification.py b/python/pyspark/ml/classification.py
index 067009559b6f..ddbca2e39b51 100644
--- a/python/pyspark/ml/classification.py
+++ b/python/pyspark/ml/classification.py
@@ -18,6 +18,7 @@
 import warnings
 
 from pyspark import since
+from pyspark.ml.base import *
 from pyspark.ml.util import *
 from pyspark.ml.wrapper import JavaEstimator, JavaModel
 from pyspark.ml.param import TypeConverters
@@ -200,7 +201,7 @@ def _checkThresholdConsistency(self):
                                  " threshold (%g) and thresholds (equivalent to %g)" % (t2, t))
 
 
-class LogisticRegressionModel(JavaModel, JavaMLWritable, JavaMLReadable):
+class LogisticRegressionModel(HasNumFeaturesModel, JavaModel, JavaMLWritable, JavaMLReadable):
     """
     Model fitted by LogisticRegression.
 
@@ -324,6 +325,8 @@ class DecisionTreeClassifier(JavaEstimator, HasFeaturesCol, HasLabelCol, HasPred
     >>> model2 = DecisionTreeClassificationModel.load(model_path)
     >>> model.featureImportances == model2.featureImportances
     True
+    >>> model.numFeatures
+    1
 
     .. versionadded:: 1.4.0
     """
@@ -373,7 +376,8 @@ def _create_model(self, java_model):
 
 
 @inherit_doc
-class DecisionTreeClassificationModel(DecisionTreeModel, JavaMLWritable, JavaMLReadable):
+class DecisionTreeClassificationModel(HasNumFeaturesModel, DecisionTreeModel, JavaMLWritable,
+                                      JavaMLReadable):
     """
     Model fitted by DecisionTreeClassifier.
 
@@ -439,6 +443,8 @@ class RandomForestClassifier(JavaEstimator, HasFeaturesCol, HasLabelCol, HasPred
     >>> test1 = sqlContext.createDataFrame([(Vectors.sparse(1, [0], [1.0]),)], ["features"])
     >>> model.transform(test1).head().prediction
     1.0
+    >>> model.numFeatures
+    1
 
     .. versionadded:: 1.4.0
     """
@@ -487,7 +493,7 @@ def _create_model(self, java_model):
         return RandomForestClassificationModel(java_model)
 
 
-class RandomForestClassificationModel(TreeEnsembleModels):
+class RandomForestClassificationModel(HasNumFeaturesModel, TreeEnsembleModels):
     """
     Model fitted by RandomForestClassifier.
 
@@ -540,6 +546,8 @@ class GBTClassifier(JavaEstimator, HasFeaturesCol, HasLabelCol, HasPredictionCol
     >>> test1 = sqlContext.createDataFrame([(Vectors.sparse(1, [0], [1.0]),)], ["features"])
     >>> model.transform(test1).head().prediction
     1.0
+    >>> model.numFeatures
+    1
 
     .. versionadded:: 1.4.0
     """
@@ -604,7 +612,7 @@ def getLossType(self):
         return self.getOrDefault(self.lossType)
 
 
-class GBTClassificationModel(TreeEnsembleModels):
+class GBTClassificationModel(HasNumFeaturesModel, TreeEnsembleModels):
     """
     Model fitted by GBTClassifier.
 
@@ -675,6 +683,8 @@ class NaiveBayes(JavaEstimator, HasFeaturesCol, HasLabelCol, HasPredictionCol, H
     True
     >>> model.theta == model2.theta
     True
+    >>> model.numFeatures
+    2
 
     .. versionadded:: 1.5.0
     """
@@ -749,7 +759,7 @@ def getModelType(self):
         return self.getOrDefault(self.modelType)
 
 
-class NaiveBayesModel(JavaModel, JavaMLWritable, JavaMLReadable):
+class NaiveBayesModel(HasNumFeaturesModel, JavaModel, JavaMLWritable, JavaMLReadable):
     """
     Model fitted by NaiveBayes.
 
@@ -817,6 +827,8 @@ class MultilayerPerceptronClassifier(JavaEstimator, HasFeaturesCol, HasLabelCol,
     True
     >>> model.weights == model2.weights
     True
+    >>> model.numFeatures
+    2
 
     .. versionadded:: 1.6.0
     """
@@ -894,7 +906,8 @@ def getBlockSize(self):
         return self.getOrDefault(self.blockSize)
 
 
-class MultilayerPerceptronClassificationModel(JavaModel, JavaMLWritable, JavaMLReadable):
+class MultilayerPerceptronClassificationModel(HasNumFeaturesModel, JavaModel, JavaMLWritable,
+                                              JavaMLReadable):
     """
     Model fitted by MultilayerPerceptronClassifier.
 
diff --git a/python/pyspark/ml/regression.py b/python/pyspark/ml/regression.py
index de8a5e4bed2e..68785671cd26 100644
--- a/python/pyspark/ml/regression.py
+++ b/python/pyspark/ml/regression.py
@@ -18,6 +18,7 @@
 import warnings
 
 from pyspark import since
+from pyspark.ml.base import HasNumFeaturesModel
 from pyspark.ml.param.shared import *
 from pyspark.ml.util import *
 from pyspark.ml.wrapper import JavaEstimator, JavaModel
@@ -80,6 +81,8 @@ class LinearRegression(JavaEstimator, HasFeaturesCol, HasLabelCol, HasPrediction
     True
     >>> model.intercept == model2.intercept
     True
+    >>> model.numFeatures
+    1
 
     .. versionadded:: 1.4.0
     """
@@ -118,7 +121,7 @@ def _create_model(self, java_model):
         return LinearRegressionModel(java_model)
 
 
-class LinearRegressionModel(JavaModel, JavaMLWritable, JavaMLReadable):
+class LinearRegressionModel(HasNumFeaturesModel, JavaModel, JavaMLWritable, JavaMLReadable):
     """
     Model fitted by LinearRegression.
 
@@ -425,6 +428,8 @@ class DecisionTreeRegressor(JavaEstimator, HasFeaturesCol, HasLabelCol, HasPredi
     True
     >>> model.depth == model2.depth
     True
+    >>> model.numFeatures
+    1
 
     .. versionadded:: 1.4.0
     """
@@ -510,7 +515,8 @@ def __repr__(self):
 
 
 @inherit_doc
-class DecisionTreeRegressionModel(DecisionTreeModel, JavaMLWritable, JavaMLReadable):
+class DecisionTreeRegressionModel(HasNumFeaturesModel, DecisionTreeModel, JavaMLWritable,
+                                  JavaMLReadable):
     """
     Model fitted by DecisionTreeRegressor.
 
@@ -564,6 +570,8 @@ class RandomForestRegressor(JavaEstimator, HasFeaturesCol, HasLabelCol, HasPredi
     >>> test1 = sqlContext.createDataFrame([(Vectors.sparse(1, [0], [1.0]),)], ["features"])
     >>> model.transform(test1).head().prediction
     0.5
+    >>> model.numFeatures
+    1
 
     .. versionadded:: 1.4.0
     """
@@ -613,7 +621,7 @@ def _create_model(self, java_model):
         return RandomForestRegressionModel(java_model)
 
 
-class RandomForestRegressionModel(TreeEnsembleModels):
+class RandomForestRegressionModel(HasNumFeaturesModel, TreeEnsembleModels):
     """
     Model fitted by RandomForestRegressor.
 
@@ -661,6 +669,8 @@ class GBTRegressor(JavaEstimator, HasFeaturesCol, HasLabelCol, HasPredictionCol,
     >>> test1 = sqlContext.createDataFrame([(Vectors.sparse(1, [0], [1.0]),)], ["features"])
     >>> model.transform(test1).head().prediction
     1.0
+    >>> model.numFeatures
+    1
 
     .. versionadded:: 1.4.0
     """
@@ -725,7 +735,7 @@ def getLossType(self):
         return self.getOrDefault(self.lossType)
 
 
-class GBTRegressionModel(TreeEnsembleModels):
+class GBTRegressionModel(HasNumFeaturesModel, TreeEnsembleModels):
     """
     Model fitted by GBTRegressor.