diff --git a/pyttb/tensor.py b/pyttb/tensor.py
index e70dcd19..340786c8 100644
--- a/pyttb/tensor.py
+++ b/pyttb/tensor.py
@@ -942,6 +942,48 @@ def ttm(self, matrix, dims=None, transpose=False):
         Y = np.transpose(Y, np.argsort(order))
         return ttb.tensor.from_data(Y)
 
+    def ttt(self, other, selfdims=None, otherdims=None):
+        """
+        Tensor mulitplication (tensor times tensor)
+
+        Parameters
+        ----------
+        other: :class:`ttb.tensor`
+        selfdims: :class:`Numpy.ndarray`, int
+        otherdims: :class:`Numpy.ndarray`, int
+        """
+
+        if not isinstance(other, tensor):
+            assert False, "other must be of type tensor"
+
+        if selfdims is None:
+            selfdims = np.array([])
+            selfshape = ()
+        else:
+            selfshape = tuple(np.array(self.shape)[selfdims])
+
+        if otherdims is None:
+            otherdims = selfdims.copy()
+            othershape = ()
+        else:
+            othershape = tuple(np.array(other.shape)[otherdims])
+
+        if not selfshape == othershape:
+            assert False, "Specified dimensions do not match"
+
+        # Compute the product
+
+        # Avoid transpose by reshaping self and computing result = self * other
+        amatrix = ttb.tenmat.from_tensor_type(self, cdims=selfdims)
+        bmatrix = ttb.tenmat.from_tensor_type(other, rdims=otherdims)
+        cmatrix = amatrix * bmatrix
+
+        # Check whether or not the result is a scalar
+        if isinstance(cmatrix, ttb.tenmat):
+            return ttb.tensor.from_tensor_type(cmatrix)
+        else:
+            return cmatrix
+
     def ttv(self, vector, dims=None):
         """
         Tensor times vector
diff --git a/tests/test_tensor.py b/tests/test_tensor.py
index 7497f352..c0c16f2d 100644
--- a/tests/test_tensor.py
+++ b/tests/test_tensor.py
@@ -1057,6 +1057,24 @@ def test_tensor_ttm(sample_tensor_2way, sample_tensor_3way, sample_tensor_4way):
         tensorInstance3.ttm(M2, tensorInstance3.ndims + 1)
     assert "dims must contain values in [0,self.dims]" in str(excinfo)
 
+@pytest.mark.indevelopment
+def test_tensor_ttt(sample_tensor_2way, sample_tensor_3way, sample_tensor_4way):
+
+    M31 = ttb.tensor.from_data(np.reshape(np.arange(1,2*3*4+1),[4,3,2], order='F'))
+    M32 = ttb.tensor.from_data(np.reshape(np.arange(1,2*3*4+1),[3,4,2], order='F'))
+
+    # outer product of M31 and M32
+    TTT1 = M31.ttt(M32)
+    assert TTT1.shape == (4,3,2,3,4,2)
+    # choose two random 2-way slices
+    data11 = np.array([1,2,3,4])
+    data12 = np.array([289,306,323,340])
+    data13 = np.array([504,528,552,576])
+    assert (TTT1[:,0,0,0,0,0].data == data11).all()
+    assert (TTT1[:,1,1,1,1,1].data == data12).all()
+    assert (TTT1[:,2,1,2,3,1].data == data13).all()
+
+
 @pytest.mark.indevelopment
 def test_tensor_ttv(sample_tensor_2way, sample_tensor_3way, sample_tensor_4way):
     (params2, tensorInstance2) = sample_tensor_2way