diff --git a/pysr/expression_specs.py b/pysr/expression_specs.py
index c7ac5327..a4c77189 100644
--- a/pysr/expression_specs.py
+++ b/pysr/expression_specs.py
@@ -63,6 +63,10 @@ def create_exports(
         """Create additional columns in the equations dataframe."""
         pass
 
+    @property
+    def evaluates_in_julia(self) -> bool:
+        return False
+
     @property
     def supports_sympy(self) -> bool:
         return False
@@ -197,6 +201,10 @@ def julia_expression_options(self):
         )
         return creator(self.function_symbols, f_combine, self.num_features)
 
+    @property
+    def evaluates_in_julia(self):
+        return True
+
     def create_exports(
         self,
         model: PySRRegressor,
@@ -219,6 +227,10 @@ def julia_expression_type(self):
     def julia_expression_options(self):
         return jl.seval("NamedTuple{(:max_parameters,)}")((self.max_parameters,))
 
+    @property
+    def evaluates_in_julia(self):
+        return True
+
     def create_exports(
         self,
         model: PySRRegressor,
diff --git a/pysr/sr.py b/pysr/sr.py
index 7fb7da01..e644d8f5 100644
--- a/pysr/sr.py
+++ b/pysr/sr.py
@@ -2313,7 +2313,10 @@ def predict(
         # feature selected) X in fit.
         X = X.reindex(columns=self.feature_names_in_)
         X = self._validate_data_X(X)
-        X = X.astype(self._get_precision_mapped_dtype(X))
+        if self.expression_spec_.evaluates_in_julia:
+            # Julia wants the right dtype
+            X = X.astype(self._get_precision_mapped_dtype(X))
+
         if category is not None:
             offset_for_julia_indexing = 1
             args: tuple = (