diff --git a/dask_expr/_categorical.py b/dask_expr/_categorical.py
index 697199242..1d17bc928 100644
--- a/dask_expr/_categorical.py
+++ b/dask_expr/_categorical.py
@@ -170,10 +170,18 @@ class Categorize(Blockwise):
 
     @functools.cached_property
     def _meta(self):
-        meta = _categorize_block(
+        return _categorize_block(
             self.frame._meta, self.operand("categories"), self.operand("index")
         )
-        return meta
+
+    def _simplify_up(self, parent, dependents):
+        result = super()._simplify_up(parent, dependents)
+        if result is None:
+            return result
+        # pop potentially dropped columns from categories
+        cats = self.operand("categories")
+        cats = {k: v for k, v in cats.items() if k in result.frame.columns}
+        return Categorize(result.frame, cats, result.operand("index"))
 
 
 class GetCategories(ApplyConcatApply):
diff --git a/dask_expr/tests/test_categorical.py b/dask_expr/tests/test_categorical.py
index 930df3884..91f586bc0 100644
--- a/dask_expr/tests/test_categorical.py
+++ b/dask_expr/tests/test_categorical.py
@@ -59,3 +59,12 @@ def test_categorical_set_index():
     d1, d2 = b.get_partition(0), b.get_partition(1)
     assert list(d1.index.compute(fuse=False)) == ["a"]
     assert list(sorted(d2.index.compute())) == ["b", "b", "c"]
+
+
+def test_categorize_drops_category_columns():
+    pdf = pd.DataFrame({"a": [1, 2, 1, 2, 3], "b": 1})
+    df = from_pandas(pdf)
+    df = df.categorize(columns=["a"])
+    result = df["b"].to_frame()
+    expected = pdf["b"].to_frame()
+    assert_eq(result, expected)