diff --git a/pyzebra/fit2.py b/pyzebra/fit2.py
index 54a463c..242149a 100644
--- a/pyzebra/fit2.py
+++ b/pyzebra/fit2.py
@@ -128,20 +128,22 @@ def fitccl(
         ("intercept", guess[4], bool(vary[4]), constraints_min[4], constraints_max[4], None, None),
     )
     # the weighted fit
-    result = mod.fit(
-        y, params, weights=[np.abs(1 / y_err[i]) for i in range(len(y_err))], x=x, calc_covar=True
-    )
-    
+    try:
+        result = mod.fit(
+            y, params, weights=[np.abs(1 / val) for val in y_err], x=x, calc_covar=True,
+        )
+    except ValueError:
+        return
+
     if result.params["g_amp"].stderr is None:
         result.params["g_amp"].stderr = result.params["g_amp"].value
     elif result.params["g_amp"].stderr > result.params["g_amp"].value:
         result.params["g_amp"].stderr = result.params["g_amp"].value
+
     # u.ufloat to work with uncertanities
     fit_area = u.ufloat(result.params["g_amp"].value, result.params["g_amp"].stderr)
     comps = result.eval_components()
 
-
-
     if len(meas["peak_indexes"]) == 0:
         # for case of no peak, there is no reason to integrate, therefore fit and int are equal
         int_area = fit_area