diff --git a/doc/source/whatsnew/v0.24.0.txt b/doc/source/whatsnew/v0.24.0.txt
index d7feb6e547b22..83f88e2c23f62 100644
--- a/doc/source/whatsnew/v0.24.0.txt
+++ b/doc/source/whatsnew/v0.24.0.txt
@@ -693,7 +693,7 @@ Groupby/Resample/Rolling
   ``SeriesGroupBy`` when the grouping variable only contains NaNs and numpy version < 1.13 (:issue:`21956`).
 - Multiple bugs in :func:`pandas.core.Rolling.min` with ``closed='left'` and a
   datetime-like index leading to incorrect results and also segfault. (:issue:`21704`)
--
+- Bug in :meth:`Resampler.apply` when passing postiional arguments to applied func (:issue:`14615`).
 
 Sparse
 ^^^^^^
diff --git a/pandas/core/resample.py b/pandas/core/resample.py
index 4a3625b2d7a2d..3b70112b8ad00 100644
--- a/pandas/core/resample.py
+++ b/pandas/core/resample.py
@@ -234,12 +234,15 @@ def pipe(self, func, *args, **kwargs):
         klass='DataFrame',
         versionadded='',
         axis=''))
-    def aggregate(self, arg, *args, **kwargs):
+    def aggregate(self, func, *args, **kwargs):
 
         self._set_binner()
-        result, how = self._aggregate(arg, *args, **kwargs)
+        result, how = self._aggregate(func, *args, **kwargs)
         if result is None:
-            result = self._groupby_and_aggregate(arg,
+            how = func
+            grouper = None
+            result = self._groupby_and_aggregate(how,
+                                                 grouper,
                                                  *args,
                                                  **kwargs)
 
@@ -852,7 +855,7 @@ def __init__(self, obj, *args, **kwargs):
         self._groupby.grouper.mutated = True
         self.groupby = copy.copy(parent.groupby)
 
-    def _apply(self, f, **kwargs):
+    def _apply(self, f, grouper=None, *args, **kwargs):
         """
         dispatch to _upsample; we are stripping all of the _upsample kwargs and
         performing the original function call on the grouped object
@@ -864,7 +867,7 @@ def func(x):
             if isinstance(f, compat.string_types):
                 return getattr(x, f)(**kwargs)
 
-            return x.apply(f, **kwargs)
+            return x.apply(f, *args, **kwargs)
 
         result = self._groupby.apply(func)
         return self._wrap_result(result)
diff --git a/pandas/tests/test_resample.py b/pandas/tests/test_resample.py
index d11077668359b..3310c97e06e3d 100644
--- a/pandas/tests/test_resample.py
+++ b/pandas/tests/test_resample.py
@@ -2165,6 +2165,28 @@ def test_resample_datetime_values(self):
         res = df['timestamp'].resample('2D').first()
         tm.assert_series_equal(res, exp)
 
+    def test_resample_apply_with_additional_args(self):
+        # GH 14615
+        def f(data, add_arg):
+            return np.mean(data) * add_arg
+
+        multiplier = 10
+        result = self.series.resample('D').apply(f, multiplier)
+        expected = self.series.resample('D').mean().multiply(multiplier)
+        tm.assert_series_equal(result, expected)
+
+        # Testing as kwarg
+        result = self.series.resample('D').apply(f, add_arg=multiplier)
+        expected = self.series.resample('D').mean().multiply(multiplier)
+        tm.assert_series_equal(result, expected)
+
+        # Testing dataframe
+        df = pd.DataFrame({"A": 1, "B": 2},
+                          index=pd.date_range('2017', periods=10))
+        result = df.groupby("A").resample("D").agg(f, multiplier)
+        expected = df.groupby("A").resample('D').mean().multiply(multiplier)
+        assert_frame_equal(result, expected)
+
 
 class TestPeriodIndex(Base):
     _index_factory = lambda x: period_range