diff --git a/nbs/core.ipynb b/nbs/core.ipynb
index 905468622..98c253b23 100644
--- a/nbs/core.ipynb
+++ b/nbs/core.ipynb
@@ -52,7 +52,7 @@
     "#export\n",
     "import inspect\n",
     "import logging\n",
-    "from concurrent.futures import ProcessPoolExecutor\n",
+    "from multiprocessing import Pool\n",
     "from functools import partial\n",
     "\n",
     "import numpy as np\n",
@@ -363,15 +363,15 @@
     "            from itertools import repeat\n",
     "            \n",
     "            xregs = repeat(None)\n",
-    "        with ProcessPoolExecutor(self.n_jobs) as executor:\n",
+    "        with Pool(self.n_jobs) as executor:\n",
     "            for model_args in self.models:\n",
     "                model, *args = _as_tuple(model_args)\n",
     "                model_name = _build_forecast_name(model, *args)\n",
     "                futures = []\n",
     "                for ga, xr in zip(gas, xregs):\n",
-    "                    future = executor.submit(ga.compute_forecasts, h, model, xr, level, *args)\n",
+    "                    future = executor.apply_async(ga.compute_forecasts, (h, model, xr, level, *args,))\n",
     "                    futures.append(future)\n",
-    "                values, keys = list(zip(*[f.result() for f in futures]))\n",
+    "                values, keys = list(zip(*[f.get() for f in futures]))\n",
     "                keys = keys[0]\n",
     "                if keys is not None:\n",
     "                    values = np.vstack(values)\n",
@@ -812,7 +812,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.12"
+   "version": "3.10.4"
   }
  },
  "nbformat": 4,
diff --git a/statsforecast/core.py b/statsforecast/core.py
index f67846cb0..a4d4efc80 100644
--- a/statsforecast/core.py
+++ b/statsforecast/core.py
@@ -5,7 +5,7 @@
 # Cell
 import inspect
 import logging
-from concurrent.futures import ProcessPoolExecutor
+from multiprocessing import Pool
 from functools import partial
 
 import numpy as np
@@ -164,15 +164,15 @@ def _data_parallel_forecast(self, h, xreg, level):
             from itertools import repeat
 
             xregs = repeat(None)
-        with ProcessPoolExecutor(self.n_jobs) as executor:
+        with Pool(self.n_jobs) as executor:
             for model_args in self.models:
                 model, *args = _as_tuple(model_args)
                 model_name = _build_forecast_name(model, *args)
                 futures = []
                 for ga, xr in zip(gas, xregs):
-                    future = executor.submit(ga.compute_forecasts, h, model, xr, level, *args)
+                    future = executor.apply_async(ga.compute_forecasts, (h, model, xr, level, *args,))
                     futures.append(future)
-                values, keys = list(zip(*[f.result() for f in futures]))
+                values, keys = list(zip(*[f.get() for f in futures]))
                 keys = keys[0]
                 if keys is not None:
                     values = np.vstack(values)