diff --git a/python/pyspark/ml/feature.py b/python/pyspark/ml/feature.py
index 64b21caa616ec..a33c3e79453e1 100755
--- a/python/pyspark/ml/feature.py
+++ b/python/pyspark/ml/feature.py
@@ -2494,21 +2494,30 @@ class RFormula(JavaEstimator, HasFeaturesCol, HasLabelCol, JavaMLReadable, JavaM
     formula = Param(Params._dummy(), "formula", "R model formula",
                     typeConverter=TypeConverters.toString)
 
+    forceIndexLabel = Param(Params._dummy(), "forceIndexLabel",
+                            "Force to index label whether it is numeric or string",
+                            typeConverter=TypeConverters.toBoolean)
+
     @keyword_only
-    def __init__(self, formula=None, featuresCol="features", labelCol="label"):
+    def __init__(self, formula=None, featuresCol="features", labelCol="label",
+                 forceIndexLabel=False):
         """
-        __init__(self, formula=None, featuresCol="features", labelCol="label")
+        __init__(self, formula=None, featuresCol="features", labelCol="label", \
+                 forceIndexLabel=False)
         """
         super(RFormula, self).__init__()
         self._java_obj = self._new_java_obj("org.apache.spark.ml.feature.RFormula", self.uid)
+        self._setDefault(forceIndexLabel=False)
         kwargs = self.__init__._input_kwargs
         self.setParams(**kwargs)
 
     @keyword_only
     @since("1.5.0")
-    def setParams(self, formula=None, featuresCol="features", labelCol="label"):
+    def setParams(self, formula=None, featuresCol="features", labelCol="label",
+                  forceIndexLabel=False):
         """
-        setParams(self, formula=None, featuresCol="features", labelCol="label")
+        setParams(self, formula=None, featuresCol="features", labelCol="label", \
+                  forceIndexLabel=False)
         Sets params for RFormula.
         """
         kwargs = self.setParams._input_kwargs
@@ -2528,6 +2537,20 @@ def getFormula(self):
         """
         return self.getOrDefault(self.formula)
 
+    @since("2.1.0")
+    def setForceIndexLabel(self, value):
+        """
+        Sets the value of :py:attr:`forceIndexLabel`.
+        """
+        return self._set(forceIndexLabel=value)
+
+    @since("2.1.0")
+    def getForceIndexLabel(self):
+        """
+        Gets the value of :py:attr:`forceIndexLabel`.
+        """
+        return self.getOrDefault(self.forceIndexLabel)
+
     def _create_model(self, java_model):
         return RFormulaModel(java_model)
 
diff --git a/python/pyspark/ml/tests.py b/python/pyspark/ml/tests.py
index e233549850888..9d46cc3b4ae64 100755
--- a/python/pyspark/ml/tests.py
+++ b/python/pyspark/ml/tests.py
@@ -477,6 +477,22 @@ def test_count_vectorizer_with_binary(self):
             feature, expected = r
             self.assertEqual(feature, expected)
 
+    def test_rformula_force_index_label(self):
+        df = self.spark.createDataFrame([
+            (1.0, 1.0, "a"),
+            (0.0, 2.0, "b"),
+            (1.0, 0.0, "a")], ["y", "x", "s"])
+        # Does not index label by default since it's numeric type.
+        rf = RFormula(formula="y ~ x + s")
+        model = rf.fit(df)
+        transformedDF = model.transform(df)
+        self.assertEqual(transformedDF.head().label, 1.0)
+        # Force to index label.
+        rf2 = RFormula(formula="y ~ x + s").setForceIndexLabel(True)
+        model2 = rf2.fit(df)
+        transformedDF2 = model2.transform(df)
+        self.assertEqual(transformedDF2.head().label, 0.0)
+
 
 class HasInducedError(Params):