diff --git a/astro/Makefile b/astro/Makefile
index 030c70e37c40..2dc25b13dc44 100644
--- a/astro/Makefile
+++ b/astro/Makefile
@@ -81,6 +81,7 @@
     SUBDIR += ptiger
     SUBDIR += py-astlib
     SUBDIR += py-astral
+    SUBDIR += py-astroML
     SUBDIR += py-astropy
     SUBDIR += py-astropy-helpers
     SUBDIR += py-ephem
diff --git a/astro/py-astroML/Makefile b/astro/py-astroML/Makefile
new file mode 100644
index 000000000000..22692a7b4f29
--- /dev/null
+++ b/astro/py-astroML/Makefile
@@ -0,0 +1,26 @@
+PORTNAME=	astroML
+PORTVERSION=	1.0.2
+CATEGORIES=	astro
+MASTER_SITES=	PYPI
+PKGNAMEPREFIX=	${PYTHON_PKGNAMEPREFIX}
+DISTFILES=	${PORTNAME}-${PORTVERSION}.post1.tar.gz
+
+MAINTAINER=	wen@FreeBSD.org
+COMMENT=	Tools for machine learning and data mining in Astronomy
+WWW=		https://www.astroml.org/
+
+LICENSE=	BSD3CLAUSE
+LICENSE_FILE=	${WRKSRC}/LICENSE.rst
+
+RUN_DEPENDS=	${PYNUMPY} \
+		${PYTHON_PKGNAMEPREFIX}scipy>=0.19:science/py-scipy@${PY_FLAVOR} \
+		${PYTHON_PKGNAMEPREFIX}matplotlib>=3.0:math/py-matplotlib@${PY_FLAVOR} \
+		${PYTHON_PKGNAMEPREFIX}scikit-learn>=0.18:science/py-scikit-learn@${PY_FLAVOR} \
+		${PYTHON_PKGNAMEPREFIX}astropy>=3.0:astro/py-astropy@${PY_FLAVOR}
+
+USES=		python:3.7+
+USE_PYTHON=	autoplist distutils
+
+WRKSRC=		${WRKDIR}/${PORTNAME}-${PORTVERSION}.post1
+
+.include <bsd.port.mk>
diff --git a/astro/py-astroML/distinfo b/astro/py-astroML/distinfo
new file mode 100644
index 000000000000..46d4afef4433
--- /dev/null
+++ b/astro/py-astroML/distinfo
@@ -0,0 +1,3 @@
+TIMESTAMP = 1677925316
+SHA256 (astroML-1.0.2.post1.tar.gz) = 45188a7a88a36ca3ec5a3aa04e5fa227f42d17415a6e168fb523375c1aabe291
+SIZE (astroML-1.0.2.post1.tar.gz) = 115119
diff --git a/astro/py-astroML/pkg-descr b/astro/py-astroML/pkg-descr
new file mode 100644
index 000000000000..cbd4133440ff
--- /dev/null
+++ b/astro/py-astroML/pkg-descr
@@ -0,0 +1,6 @@
+AstroML is a Python module for machine learning and data mining built on
+numpy, scipy, scikit-learn, and matplotlib, and distributed under the BSD
+license. It contains a growing library of statistical and machine learning
+routines for analyzing astronomical data in python, loaders for several
+open astronomical datasets, and a large suite of examples of analyzing and
+visualizing astronomical datasets.