diff --git a/science/py-PyFR/Makefile b/science/py-PyFR/Makefile
index aa3e353fbd68..89d1ff43f7ac 100644
--- a/science/py-PyFR/Makefile
+++ b/science/py-PyFR/Makefile
@@ -1,44 +1,45 @@
 PORTNAME=	PyFR
-DISTVERSION=	1.12.3
+DISTVERSION=	1.13.0
 CATEGORIES=	science python
 MASTER_SITES=	CHEESESHOP
 PKGNAMEPREFIX=	${PYTHON_PKGNAMEPREFIX}
 DISTNAME=	pyfr-${DISTVERSION}
 
 MAINTAINER=	yuri@FreeBSD.org
 COMMENT=	Framework for solving advection-diffusion type problems
 
 LICENSE=	BSD3CLAUSE
 
 RUN_DEPENDS=	${PYTHON_PKGNAMEPREFIX}appdirs>=1.4.0:devel/py-appdirs@${PY_FLAVOR} \
-		${PYTHON_PKGNAMEPREFIX}gimmik>=2.0:math/py-gimmik@${PY_FLAVOR} \
+		${PYTHON_PKGNAMEPREFIX}gimmik>=2.2:math/py-gimmik@${PY_FLAVOR} \
 		${PYTHON_PKGNAMEPREFIX}h5py>=2.10:science/py-h5py@${PY_FLAVOR} \
 		${PYTHON_PKGNAMEPREFIX}mako>=1.0.0:textproc/py-mako@${PY_FLAVOR} \
-		${PYTHON_PKGNAMEPREFIX}mpi4py>=3.0:net/py-mpi4py@${PY_FLAVOR} \
+		${PYTHON_PKGNAMEPREFIX}mpi4py>=3.1.0:net/py-mpi4py@${PY_FLAVOR} \
+		${PYTHON_PKGNAMEPREFIX}platformdirs>=2.2.0:devel/py-platformdirs@${PY_FLAVOR} \
 		${PYTHON_PKGNAMEPREFIX}pytools>=2016.2.1:devel/py-pytools@${PY_FLAVOR} \
 		${PYNUMPY}
 
 USES=		python:3.7+ shebangfix
 USE_PYTHON=	distutils concurrent autoplist
 
 SHEBANG_FILES=	setup.py pyfr/__main__.py
 
 NO_ARCH=	yes
 
 OPTIONS_MULTI=		PARALLEL
 OPTIONS_MULTI_PARALLEL=	OPENCL OPENMP # CUDA isn't supported on FreeBSD
 OPTIONS_DEFAULT=	${OPTIONS_MULTI_PARALLEL}
 PARALLEL_DESC=		Parallelization backends to install
 
 OPENCL_RUN_DEPENDS=	${PYTHON_PKGNAMEPREFIX}pyopencl>0:devel/py-pyopencl@${PY_FLAVOR} \
 			clblas>0:math/clblas
 OPENMP_RUN_DEPENDS=	libxsmm>0:math/libxsmm
 
 pre-build: # patch in pre-build to make the patch less error-prone (it has %%LOCALBASE%%)
 	@${REINPLACE_CMD} 's|%%LOCALBASE%%|${LOCALBASE}|' ${WRKSRC}/pyfr/backends/openmp/compiler.py
 
 post-install: # workaround: https://groups.google.com/forum/#!topic/pyfrmailinglist/RNi_LcizGBo
 	@${RM} ${STAGEDIR}${PREFIX}/__main__.py
 	@${REINPLACE_CMD} 's|^${PREFIX}/__main__\.py||' ${_PYTHONPKGLIST}
 
 .include <bsd.port.mk>
diff --git a/science/py-PyFR/distinfo b/science/py-PyFR/distinfo
index a58d89e6b52a..a97f23e579cf 100644
--- a/science/py-PyFR/distinfo
+++ b/science/py-PyFR/distinfo
@@ -1,3 +1,3 @@
-TIMESTAMP = 1637539255
-SHA256 (pyfr-1.12.3.tar.gz) = fdf7bfd62b0f31f2dfaeff205095bc9d71a19a13128e9ca0ee5b0fbad2471cc2
-SIZE (pyfr-1.12.3.tar.gz) = 294826
+TIMESTAMP = 1645861007
+SHA256 (pyfr-1.13.0.tar.gz) = ac6ecec738d4e23799ab8c50dea9bdbd7d37bc971bd33f22720c5a230b8e7b2f
+SIZE (pyfr-1.13.0.tar.gz) = 293344
diff --git a/science/py-PyFR/pkg-descr b/science/py-PyFR/pkg-descr
index e851ff3eee74..29886c9d0e7b 100644
--- a/science/py-PyFR/pkg-descr
+++ b/science/py-PyFR/pkg-descr
@@ -1,20 +1,20 @@
 PyFR is an open-source Python based framework for solving advection-diffusion
 type problems on streaming architectures using the Flux Reconstruction approach
 of Huynh. The framework is designed to solve a range of governing systems on
 mixed unstructured grids containing various element types. It is also designed
 to target a range of hardware platforms via use of an in-built domain specific
 language derived from the Mako templating engine. The current release has the
 following capabilities:
 * Governing Equations - Euler, Navier Stokes
 * Dimensionality - 2D, 3D
 * Element Types - Triangles, Quadrilaterals, Hexahedra, Prisms, Tetrahedra,
   Pyramids
 * Platforms - CPU Clusters, Nvidia GPU Clusters, AMD GPU Clusters, Intel Xeon
   Phi Clusters
 * Spatial Discretisation - High-Order Flux Reconstruction
 * Temporal Discretisation - Explicit and Implicit (via Dual Time-Stepping)
 * Precision - Single, Double
 * Mesh Files Imported - Gmsh (.msh), CGNS (.cgns)
 * Solution Files Exported - Unstructured VTK (.vtu, .pvtu)
 
-WWW: http://www.pyfr.org/
+WWW: https://www.pyfr.org/