diff --git a/pymc_experimental/tests/test_prior_from_trace.py b/pymc_experimental/tests/test_prior_from_trace.py
index ee2461062..f6bcd3663 100644
--- a/pymc_experimental/tests/test_prior_from_trace.py
+++ b/pymc_experimental/tests/test_prior_from_trace.py
@@ -163,3 +163,9 @@ def test_prior_from_idata(idata, user_param_cfg, coords, param_cfg):
         test_prior = pm.sample_prior_predictive(1)
     names = [p["name"] for p in param_cfg.values()]
     assert set(model.named_vars) == {"trace_prior_", *names}
+
+
+def test_empty(idata, coords):
+    with pm.Model(coords=coords):
+        priors = pmx.utils.prior.prior_from_idata(idata)
+        assert not priors
diff --git a/pymc_experimental/utils/prior.py b/pymc_experimental/utils/prior.py
index 73a3b00b7..962b01bc0 100644
--- a/pymc_experimental/utils/prior.py
+++ b/pymc_experimental/utils/prior.py
@@ -132,7 +132,7 @@ def prior_from_idata(
     idata: arviz.InferenceData,
     name="trace_prior_",
     *,
-    var_names: Sequence[str],
+    var_names: Sequence[str] = (),
     **kwargs: Union[ParamCfg, RVTransform, str, Tuple]
 ) -> Dict[str, pt.TensorVariable]:
     """
@@ -192,5 +192,7 @@ def prior_from_idata(
     ...     trace1 = pm.sample_prior_predictive(100)
     """
     param_cfg = _parse_args(var_names=var_names, **kwargs)
+    if not param_cfg:
+        return {}
     flat_info = _flatten(idata, **param_cfg)
     return _mvn_prior_from_flat_info(name, flat_info)