diff --git a/skpro/distributions/halfcauchy.py b/skpro/distributions/halfcauchy.py
index e1a97d5fd..056987ddd 100644
--- a/skpro/distributions/halfcauchy.py
+++ b/skpro/distributions/halfcauchy.py
@@ -67,7 +67,7 @@ def _get_scipy_object(self) -> rv_continuous:
 
     def _get_scipy_param(self):
         beta = self._bc_params["beta"]
-        return [beta], {}
+        return [], {"scale": beta}
 
     @classmethod
     def get_test_params(cls, parameter_set="default"):
diff --git a/skpro/distributions/tests/test_halfcauchy.py b/skpro/distributions/tests/test_halfcauchy.py
new file mode 100644
index 000000000..cbc988d99
--- /dev/null
+++ b/skpro/distributions/tests/test_halfcauchy.py
@@ -0,0 +1,71 @@
+"""Tests for HalfCauchy distribution."""
+# copyright: skpro developers, BSD-3-Clause License (see LICENSE file)
+
+import numpy as np
+import pandas as pd
+import pytest
+from numpy.testing import assert_allclose
+from scipy.stats import halfcauchy
+
+from skpro.distributions.halfcauchy import HalfCauchy
+from skpro.tests.test_switch import run_test_module_changed
+
+
+@pytest.mark.skipif(
+    not run_test_module_changed("skpro.distributions"),
+    reason="run only if skpro.distributions has been changed",
+)
+def test_halfcauchy_scalar_matches_scipy():
+    """HalfCauchy scalar pdf/cdf/ppf should match scipy implementation."""
+    beta = 2.5
+    dist = HalfCauchy(beta=beta)
+
+    x = 1.7
+    p = 0.8
+
+    assert_allclose(dist.pdf(x), halfcauchy.pdf(x, scale=beta), rtol=1e-12)
+    assert_allclose(dist.cdf(x), halfcauchy.cdf(x, scale=beta), rtol=1e-12)
+    assert_allclose(dist.ppf(p), halfcauchy.ppf(p, scale=beta), rtol=1e-12)
+
+    # Check support behavior (x < 0 outside support)
+    assert_allclose(dist.pdf(-1.0), 0.0, atol=1e-15)
+    assert_allclose(dist.cdf(-1.0), 0.0, atol=1e-15)
+
+
+@pytest.mark.skipif(
+    not run_test_module_changed("skpro.distributions"),
+    reason="run only if skpro.distributions has been changed",
+)
+def test_halfcauchy_broadcast_and_shape():
+    """HalfCauchy should broadcast and preserve shape/index/columns."""
+    beta = [[1.0, 2.0], [3.0, 4.0]]
+    dist = HalfCauchy(beta=beta)
+
+    x = pd.DataFrame([[0.5, 1.0], [2.0, 3.0]], index=dist.index, columns=dist.columns)
+    p = pd.DataFrame([[0.1, 0.2], [0.7, 0.9]], index=dist.index, columns=dist.columns)
+
+    pdf = dist.pdf(x)
+    cdf = dist.cdf(x)
+    ppf = dist.ppf(p)
+
+    assert isinstance(pdf, pd.DataFrame)
+    assert isinstance(cdf, pd.DataFrame)
+    assert isinstance(ppf, pd.DataFrame)
+
+    assert pdf.shape == dist.shape
+    assert cdf.shape == dist.shape
+    assert ppf.shape == dist.shape
+
+    assert pdf.index.equals(dist.index)
+    assert cdf.index.equals(dist.index)
+    assert ppf.index.equals(dist.index)
+
+    assert pdf.columns.equals(dist.columns)
+    assert cdf.columns.equals(dist.columns)
+    assert ppf.columns.equals(dist.columns)
+
+    beta_np = np.asarray(beta)
+
+    assert_allclose(pdf.to_numpy(), halfcauchy.pdf(x.to_numpy(), scale=beta_np), rtol=1e-12)
+    assert_allclose(cdf.to_numpy(), halfcauchy.cdf(x.to_numpy(), scale=beta_np), rtol=1e-12)
+    assert_allclose(ppf.to_numpy(), halfcauchy.ppf(p.to_numpy(), scale=beta_np), rtol=1e-12)