diff --git a/README.md b/README.md
index 32ab9243..709ce83c 100644
--- a/README.md
+++ b/README.md
@@ -23,7 +23,7 @@ NNS is built around partial moments, the lower and upper components of variance,
 |---|---|
 | Distribution package | `ovvo-nns` |
 | Import package | `nns` |
-| Current version | `1.2.0` |
+| Current version | `1.3.0` |
 | Python | `>=3.11` |
 | Required runtime dependencies | NumPy, SciPy |
 | R required at runtime | No |
diff --git a/pyproject.toml b/pyproject.toml
index 537ffbb2..a961bb11 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,6 @@
 [project]
 name = "ovvo-nns"
-version = "1.2.0"
+version = "1.3.0"
 description = "Python port of nonlinear nonparametric statistics from R NNS"
 readme = "README.md"
 requires-python = ">=3.11"
diff --git a/src/nns/__init__.py b/src/nns/__init__.py
index a24cf3e6..8882f54d 100644
--- a/src/nns/__init__.py
+++ b/src/nns/__init__.py
@@ -4,7 +4,7 @@
 
 from nns.pm_matrix import pm_matrix as pm_matrix
 
-__version__ = "1.2.0"
+__version__ = "1.3.0"
 
 _EXPORTS = {
     "BoostResult": ("nns.boost", "BoostResult"),
diff --git a/tests/benchmarks/_r_baseline.json b/tests/benchmarks/_r_baseline.json
index 6bf3fc65..9b41ac95 100644
--- a/tests/benchmarks/_r_baseline.json
+++ b/tests/benchmarks/_r_baseline.json
@@ -78,6 +78,6 @@
     "pm_matrix_50x500_seconds": 0.0072,
     "sd_efficient_set_50x252_degree2_seconds": 0.0044
   },
-  "nns_version": "12.1",
+  "nns_version": "13.0",
   "schema_version": 1
 }
diff --git a/tests/benchmarks/test_lpm.py b/tests/benchmarks/test_lpm.py
index e3eae3e7..9a8466ab 100644
--- a/tests/benchmarks/test_lpm.py
+++ b/tests/benchmarks/test_lpm.py
@@ -896,7 +896,6 @@ def test_nns_boost_factor_predictor_50x2(
         variable[:10],
         learner_trials=10,
         cv_size=0.25,
-        factor_levels=(["low", "mid", "high"], None),
         feature_importance=False,
     )
 
@@ -926,7 +925,6 @@ def test_nns_boost_multi_factor_predictor_50x3(
         variable[:10],
         learner_trials=10,
         cv_size=0.25,
-        factor_levels=(["low", "mid", "high"], None, ["down", "up"]),
         feature_importance=False,
         random_seed=1,
     )
diff --git a/tests/invariants/test_stack.py b/tests/invariants/test_stack.py
index 9e3471dd..99d02a67 100644
--- a/tests/invariants/test_stack.py
+++ b/tests/invariants/test_stack.py
@@ -36,6 +36,21 @@ def test_nns_stack_numeric_shapes_and_keys() -> None:
     assert np.all(np.isfinite(result["stack"]))
 
 
+def test_nns_stack_accepts_duplicate_predictor_columns() -> None:
+    # Parity with nns_reg: the cbind(x, x) dimension trick must work for
+    # nns_stack too. R NNS.stack historically rejected duplicate predictor
+    # names ("[IVs.train] predictor names must be unique."); the Python port
+    # never had that restriction and must keep accepting duplicate columns in
+    # both the training matrix and the point-estimate matrix.
+    rng = np.random.default_rng(123)
+    x = rng.standard_normal(60)
+    y = rng.standard_normal(60)
+    variable = np.column_stack((x, x))
+
+    result = nns_stack(variable, y, variable[:5], method=(1,), folds=2, cv_size=0.25)
+
+    assert result["reg"].shape == (5,)
+    assert np.all(np.isfinite(result["reg"]))
 
 
 def test_nns_stack_pred_int_falls_back_to_point_estimate_when_regression_drops_rows() -> None:
diff --git a/uv.lock b/uv.lock
index 614f14ec..0985a78d 100644
--- a/uv.lock
+++ b/uv.lock
@@ -1044,7 +1044,7 @@ wheels = [
 
 [[package]]
 name = "ovvo-nns"
-version = "1.2.0"
+version = "1.3.0"
 source = { editable = "." }
 dependencies = [
     { name = "matplotlib" },