diff --git a/python/snewpy/models/ccsn.py b/python/snewpy/models/ccsn.py
index 3ae5b8d3f..d6b2bf4f9 100644
--- a/python/snewpy/models/ccsn.py
+++ b/python/snewpy/models/ccsn.py
@@ -414,6 +414,7 @@ def __init__(self, progenitor_mass:u.Quantity):
 
 _fornax_2022_masses = [float(p.strip('.bh')) for p in _fornax_2022_progenitors] << u.Msun
 
+
 @RegistryModel(progenitor_mass = _fornax_2022_masses )
 class Fornax_2022(loaders.Fornax_2022):
     """Model based on 2D simulations of 100 progenitors from Tianshu Wang, David Vartanyan, Adam Burrows, and Matthew S.B. Coleman, MNRAS 517:543, 2022.
@@ -429,6 +430,31 @@ def __init__(self, progenitor_mass:u.Quantity):
         return super().__init__(filename, self.metadata)
 
 
+_fornax_2024_progenitors = [
+                'u8.1',  '9a',    '9b',     '9.25',  '9.5',
+                'z9.6',  '11',    '12.25',  '14',    '15.01',
+                '16.5',  '16',    '17',     '18',    '18.5',
+                '19',    '19.56', '20',     '21.68', '23',
+                '24',    '25',    '40',     '60',    '100']
+
+_fornax_2024_masses = [float(re.sub('[A-Za-z]', '', p)) for p in _fornax_2024_progenitors] << u.Msun
+
+
+@RegistryModel(progenitor_mass = _fornax_2022_masses )
+class Fornax_2024(loaders.Fornax_2024):
+    """Model based on 3D simulations of 25 progenitors using the Fornax code.
+       Data available at https://www.astro.princeton.edu/~burrows/nu-emissions.3d.update/
+       """
+    #a mapping of mass to the progenitor
+    _mass_to_progenitor = dict(zip(_fornax_2024_masses,_fornax_2024_progenitors))
+
+    def __init__(self, progenitor_mass:u.Quantity):
+        progenitor = self._mass_to_progenitor[progenitor_mass]
+        self.metadata['Black hole'] = progenitor == '12.25' or progenitor == '14' or progenitor == '19.56' or progenitor == '40'
+        filename = f'lum_spec_{progenitor}_dat.h5'
+        return super().__init__(filename, self.metadata)
+
+
 @RegistryModel(
                _param_validator = lambda p: \
                (p['axion_mass'] == 0 and p['axion_coupling'] == 0) or \
diff --git a/python/snewpy/models/ccsn_loaders.py b/python/snewpy/models/ccsn_loaders.py
index ecda9b0c6..01ab84be2 100644
--- a/python/snewpy/models/ccsn_loaders.py
+++ b/python/snewpy/models/ccsn_loaders.py
@@ -815,6 +815,53 @@ def __init__(self, filename, metadata={}):
             self.luminosity[flavor] = np.sum(dLdE*dE, axis=1) * factor * 1e50 * u.erg/u.s
 
 
+class Fornax_2024(Fornax_2021):
+    def __init__(self, filename, metadata={}):
+        """
+        Parameters
+        ----------
+        filename : str
+            Absolute or relative path to HDF5 file with model data.
+        """
+        # Open the requested filename using the model downloader.
+        datafile = self.request_file(filename)
+        # Set up model metadata.
+        self.progenitor = os.path.splitext(os.path.basename(filename))[0].split('_')[2]
+        self.progenitor_mass = float(re.sub('[A-Za-z]', '', self.progenitor))
+
+        self.metadata = metadata
+
+        # Open HDF5 data file.
+        _h5file = h5py.File(datafile, 'r')
+
+        self.metadata['PNS mass'] = _h5file.attrs['Mpns'] * u.Msun
+        self.time = _h5file['nu0'].attrs['time'] * u.s
+
+        self.luminosity = {}
+        self._E = {}
+        self._dLdE = {}
+        for flavor in Flavor:
+            # Convert flavor to key name in the model HDF5 file
+            key = {Flavor.NU_E: 'nu0',
+                   Flavor.NU_E_BAR: 'nu1',
+                   Flavor.NU_X: 'nu2',
+                   Flavor.NU_X_BAR: 'nu2'}[flavor]
+
+            self._E[flavor] = np.asarray(_h5file[key]['egroup'])
+            self._dLdE[flavor] = {f"g{i}": np.asarray(_h5file[key][f'g{i}']) for i in range(12)}
+
+            # Compute luminosity by integrating over model energy bins.
+            dE = np.asarray(_h5file[key]['degroup'])
+            n = len(dE[0])
+            dLdE = np.zeros((len(self.time), n), dtype=float)
+            for i in range(n):
+                dLdE[:, i] = self._dLdE[flavor][f"g{i}"]
+
+            # Note factor of 0.25 in nu_x and nu_x_bar.
+            factor = 1. if flavor.is_electron else 0.25
+            self.luminosity[flavor] = np.sum(dLdE*dE, axis=1) * factor * 1e50 * u.erg/u.s
+
+
 class Mori_2023(PinchedModel):
     def __init__(self, filename, metadata={}):
         """
diff --git a/python/snewpy/models/model_files.yml b/python/snewpy/models/model_files.yml
index 3e9b9840d..caf656415 100644
--- a/python/snewpy/models/model_files.yml
+++ b/python/snewpy/models/model_files.yml
@@ -5,6 +5,7 @@
 config:
     - &snewpy "https://github.com/SNEWS2/snewpy/raw/v{snewpy_version}/models/{model}/{filename}"
     - &ccsn_repository "https://github.com/SNEWS2/snewpy-models-ccsn/raw/v0.3/models/{model}/{filename}"
+    - &fnx_repository "https://github.com/SNEWS2/snewpy-models-ccsn/raw/fornax-2024-update/models/{model}/{filename}"
     - &presn_repository "https://github.com/SNEWS2/snewpy-models-presn/raw/v0.2/models/{model}/{filename}"
     
 models:
@@ -21,6 +22,9 @@ models:
         Fornax_2022: 
             repository: *ccsn_repository
     
+        Fornax_2024: 
+            repository: *fnx_repository
+    
         Kuroda_2020: 
             repository: *ccsn_repository