diff --git a/doc/source/whatsnew/v3.0.0.rst b/doc/source/whatsnew/v3.0.0.rst
index 099e5bc48353a..5254b0de83b5a 100644
--- a/doc/source/whatsnew/v3.0.0.rst
+++ b/doc/source/whatsnew/v3.0.0.rst
@@ -847,6 +847,7 @@ Reshaping
 - Bug in :meth:`DataFrame.stack` with the new implementation where ``ValueError`` is raised when ``level=[]`` (:issue:`60740`)
 - Bug in :meth:`DataFrame.unstack` producing incorrect results when manipulating empty :class:`DataFrame` with an :class:`ExtentionDtype` (:issue:`59123`)
 - Bug in :meth:`concat` where concatenating DataFrame and Series with ``ignore_index = True`` drops the series name (:issue:`60723`, :issue:`56257`)
+- Bug in :func:`melt` where calling with duplicate column names in ``id_vars`` raised a misleading ``AttributeError`` (:issue:`61475`)
 
 Sparse
 ^^^^^^
diff --git a/pandas/core/reshape/melt.py b/pandas/core/reshape/melt.py
index f4cb82816bbcf..2683c407d404d 100644
--- a/pandas/core/reshape/melt.py
+++ b/pandas/core/reshape/melt.py
@@ -239,6 +239,9 @@ def melt(
     mdata: dict[Hashable, AnyArrayLike] = {}
     for col in id_vars:
         id_data = frame.pop(col)
+        # GH61475 - prevent AttributeError when duplicate column
+        if not hasattr(id_data, "dtype"):
+            raise Exception(f"{col} is a duplicate column header")
         if not isinstance(id_data.dtype, np.dtype):
             # i.e. ExtensionDtype
             if num_cols_adjusted > 0:
diff --git a/pandas/tests/reshape/test_melt.py b/pandas/tests/reshape/test_melt.py
index 95aa5291cb45a..3d49394352c8a 100644
--- a/pandas/tests/reshape/test_melt.py
+++ b/pandas/tests/reshape/test_melt.py
@@ -555,6 +555,14 @@ def test_melt_multiindex_columns_var_name_too_many(self):
         ):
             df.melt(var_name=["first", "second", "third"])
 
+    def test_melt_duplicate_column_header_raises(self):
+        # GH61475
+        df = DataFrame([[1, 2, 3], [3, 4, 5]], columns=["A", "A", "B"])
+        msg = "A is a duplicate column header"
+
+        with pytest.raises(Exception, match=msg):
+            df.melt(id_vars=["A"], value_vars=["B"])
+
 
 class TestLreshape:
     def test_pairs(self):