diff --git a/python/prophet/forecaster.py b/python/prophet/forecaster.py
index 261776c85..7f404b4c4 100644
--- a/python/prophet/forecaster.py
+++ b/python/prophet/forecaster.py
@@ -914,6 +914,10 @@ def add_seasonality(
             ps = float(prior_scale)
         if ps <= 0:
             raise ValueError('Prior scale must be > 0')
+        if not period > 0:
+            # Also rejects NaN. period divides the Fourier frequencies, so 0
+            # only failed later in fit with a ZeroDivisionError.
+            raise ValueError('Period must be > 0')
         if fourier_order <= 0:
             raise ValueError('Fourier Order must be > 0')
         if mode is None:
diff --git a/python/prophet/tests/test_prophet.py b/python/prophet/tests/test_prophet.py
index 0c5e9d0e2..2488308b3 100644
--- a/python/prophet/tests/test_prophet.py
+++ b/python/prophet/tests/test_prophet.py
@@ -688,6 +688,14 @@ def test_custom_fourier_order(self, backend):
         with pytest.raises(ValueError):
             m.add_seasonality(name="weekly", period=7, fourier_order=-1)
 
+    def test_custom_period(self, backend):
+        """Period must be > 0"""
+        m = Prophet(stan_backend=backend)
+        for period in [0, 0.0, -7, float("nan")]:
+            with pytest.raises(ValueError, match="Period must be > 0"):
+                m.add_seasonality(name="custom", period=period, fourier_order=3)
+        assert "custom" not in m.seasonalities
+
     def test_custom_priors(self, daily_univariate_ts, backend):
         holidays = pd.DataFrame(
             {