diff --git a/src/marvin/utilities/types.py b/src/marvin/utilities/types.py
index f8c6e6e8c..08570678b 100644
--- a/src/marvin/utilities/types.py
+++ b/src/marvin/utilities/types.py
@@ -14,6 +14,7 @@
     TypeVar,
     get_args,
     get_origin,
+    get_type_hints,
 )
 
 from marvin.utilities.asyncio import run_sync
@@ -356,13 +357,27 @@ def from_function(
             else:
                 raise
 
+        # `inspect.signature` returns string annotations when the module that
+        # defined `func` uses `from __future__ import annotations` (PEP 563).
+        # `typing.get_type_hints` resolves those forward references back to the
+        # actual types, so the downstream LLM call receives a real type object
+        # (e.g. `Recipe`) rather than the raw string `'Recipe'`.
+        # Fall back to `sig.return_annotation` if resolution fails (e.g. the
+        # type is not importable in the current scope).
+        # See https://github.com/PrefectHQ/marvin/issues/950
+        try:
+            hints = get_type_hints(func)
+            resolved_return = hints.get("return", sig.return_annotation)
+        except Exception:
+            resolved_return = sig.return_annotation
+
         function_dict: dict[str, Any] = {
             "function": func,
             "signature": sig,
             "name": name,
             "docstring": inspect.cleandoc(docstring) if docstring else None,
             "parameters": parameters,
-            "return_annotation": sig.return_annotation,
+            "return_annotation": resolved_return,
             "source_code": source_code,
         }
 
diff --git a/tests/basic/utilities/test_types.py b/tests/basic/utilities/test_types.py
index 86bf10633..129f9f0d5 100644
--- a/tests/basic/utilities/test_types.py
+++ b/tests/basic/utilities/test_types.py
@@ -132,3 +132,54 @@ def test_labels_indexed_labels(self):
             1: "42",
             2: "True",
         }
+
+
+class TestPythonFunctionFromFutureAnnotations:
+    """Regression test for https://github.com/PrefectHQ/marvin/issues/950
+
+    When a module uses `from __future__ import annotations` (PEP 563), all
+    annotations are stored as strings rather than the actual types.
+    `PythonFunction.from_function` must resolve them with `typing.get_type_hints`
+    so that downstream LLM calls receive a real type, not the string 'Recipe'.
+    """
+
+    def test_string_annotation_is_resolved_to_type(self):
+        """A string return annotation must resolve to the actual type class."""
+        from pydantic import BaseModel
+        from marvin.utilities.types import PythonFunction
+
+        class Dish(BaseModel):
+            name: str
+
+        # Mimic what `from __future__ import annotations` does: the annotation
+        # stored on the function is a string, not the type object.
+        def make_dish(ingredients: list[str]) -> "Dish":
+            """Return a dish made from the given ingredients."""
+
+        model = PythonFunction.from_function(make_dish)
+
+        # Before the fix: return_annotation was the string 'Dish'
+        # After the fix: it must be the actual Dish class
+        assert model.return_annotation is Dish, (
+            f"Expected return_annotation to be the Dish class, got {model.return_annotation!r}. "
+            "Hint: 'from __future__ import annotations' converts annotations to strings; "
+            "PythonFunction.from_function must resolve them via typing.get_type_hints()."
+        )
+
+    def test_non_string_annotation_still_works(self):
+        """A normal (non-string) annotation must continue to work unchanged."""
+        from pydantic import BaseModel
+        from marvin.utilities.types import PythonFunction
+
+        class Ingredient(BaseModel):
+            name: str
+
+        # Normal annotation without PEP 563 — sig.return_annotation is already
+        # the class object.
+        def list_ingredients(query: str) -> list[Ingredient]:
+            """List ingredients matching the query."""
+
+        model = PythonFunction.from_function(list_ingredients)
+        import typing
+        # The origin must be list (list[Ingredient])
+        assert typing.get_origin(model.return_annotation) is list