diff --git a/skimage/measure/tests/test_fit.py b/skimage/measure/tests/test_fit.py
index 137a6e44..c3750789 100644
--- a/skimage/measure/tests/test_fit.py
+++ b/skimage/measure/tests/test_fit.py
@@ -39,5 +39,42 @@ def test_line_model_estimate():
     assert_almost_equal(model0._params, model_est._params, 1)
 
 
+def test_circle_model_invalid_input():
+    assert_raises(ValueError, CircleModel().estimate, np.empty((5, 3)))
+
+
+def test_circle_model_predict():
+    model = CircleModel()
+    r = 5
+    model._params = (0, 0, r)
+    t = np.arange(0, 2 * np.pi, np.pi / 2)
+
+    xy = np.array(((5, 0), (0, 5), (-5, 0), (0, -5)))
+    assert_almost_equal(xy, model.predict_xy(t))
+
+
+def test_circle_model_is_degenerate():
+    assert_equal(CircleModel().is_degenerate(np.empty((1, 2))), True)
+
+
+def test_circle_model_estimate():
+    # generate original data without noise
+    model0 = CircleModel()
+    model0._params = (10, 12, 3)
+    t = np.linspace(0, 2 * np.pi, 1000)
+    data0 = model0.predict_xy(t)
+
+    # add gaussian noise to data
+    np.random.seed(1234)
+    data = data0 + np.random.normal(size=data0.shape)
+
+    # estimate parameters of noisy data
+    model_est = CircleModel()
+    model_est.estimate(data)
+
+    # test whether estimated parameters almost equals original parameters
+    assert_almost_equal(model0._params, model_est._params, 1)
+
+
 if __name__ == "__main__":
     np.testing.run_module_suite()