diff --git a/jdaviz/configs/default/plugins/model_fitting/tests/test_fitting.py b/jdaviz/configs/default/plugins/model_fitting/tests/test_fitting.py
index 308c8739b6..81f0d959d5 100644
--- a/jdaviz/configs/default/plugins/model_fitting/tests/test_fitting.py
+++ b/jdaviz/configs/default/plugins/model_fitting/tests/test_fitting.py
@@ -31,12 +31,20 @@ def test_model_params():
     model_parameters = {"Gaussian1D": ["amplitude", "stddev", "mean"],
                         "Const1D": ["amplitude"],
                         "Linear1D": ["slope", "intercept"],
+                        "Polynomial1D": ["c0", "c1"],
                         "PowerLaw1D": ["amplitude", "x_0", "alpha"],
                         "Lorentz1D": ["amplitude", "x_0", "fwhm"],
                         "Voigt1D": ["x_0", "amplitude_L", "fwhm_L", "fwhm_G"],
+                        "BlackBody": ["temperature", "scale"],
                         }
 
-    for model_name, expected_params in model_parameters.items():
+    for model_name in initializers.MODELS.keys():
+        if model_name not in model_parameters.keys():
+            # this would be caught later by the assertion anyways,
+            # but raising an error will be more clear that the
+            # test needs to be updated rather than the code breaking
+            raise ValueError(f"{model_name} not in test dictionary of expected parameters")
+        expected_params = model_parameters.get(model_name, [])
         params = initializers.get_model_parameters(model_name)
         assert len(params) == len(expected_params)
         assert np.all([p in expected_params for p in params])