diff --git a/bindings/distrdf/python/DistRDF/Backends/Dask/Backend.py b/bindings/distrdf/python/DistRDF/Backends/Dask/Backend.py
index 84a9a0bbd4abc..5e3da6ad5a836 100644
--- a/bindings/distrdf/python/DistRDF/Backends/Dask/Backend.py
+++ b/bindings/distrdf/python/DistRDF/Backends/Dask/Backend.py
@@ -104,6 +104,20 @@ def __init__(self, daskclient: Optional[Client] = None):
         # N is the number of cores on the local machine.
         self.client = (daskclient if daskclient is not None else
                        Client(LocalCluster(n_workers=os.cpu_count(), threads_per_worker=1, processes=True)))
+        
+        workers = self.client.scheduler_info().get("workers", None)
+
+        if workers is None:
+            return
+
+        for worker in workers.values():
+            threads = worker.get("nthreads", 1)
+
+            if threads > 1:
+                raise RuntimeError(
+                    "DistRDF with Dask does not support threaded workers. "
+                    "Please use processes=True and threads_per_worker=1."
+                )
 
     def optimize_npartitions(self) -> int:
         """
diff --git a/roottest/python/distrdf/backends/check_backend.py b/roottest/python/distrdf/backends/check_backend.py
index b7ae271ca26ea..f8d15ee313dff 100644
--- a/roottest/python/distrdf/backends/check_backend.py
+++ b/roottest/python/distrdf/backends/check_backend.py
@@ -59,6 +59,50 @@ def test_optimize_npartitions(self, payload):
             backend = Backend.SparkBackend(sparkcontext=connection)
             assert backend.optimize_npartitions() == 2
 
+    def test_dask_backend_handles_missing_workers(self, payload):
+        """
+        Check that DaskBackend initialization succeeds when scheduler_info
+        does not provide worker information.
+        """
+        connection, backend = payload
+
+        if backend != "dask":
+            return
+
+        from ROOT._distrdf.Backends.Dask import Backend
+
+        original_scheduler_info = connection.scheduler_info
+
+        try:
+            connection.scheduler_info = lambda: {}
+
+            backend = Backend.DaskBackend(daskclient=connection)
+            assert backend.client is connection
+
+            df = ROOT.RDataFrame(10, executor=connection)
+            assert df.Count().GetValue() == 10
+
+        finally:
+            connection.scheduler_info = original_scheduler_info
+
+    def test_dask_backend_rejects_threaded_workers(self):
+        """
+        Check that DaskBackend rejects threaded workers.
+        """
+        from dask.distributed import Client, LocalCluster
+        from ROOT._distrdf.Backends.Dask import Backend
+
+        cluster = LocalCluster(n_workers=1, threads_per_worker=2, processes=False)
+        client = Client(cluster)
+
+        try:
+            with pytest.raises(RuntimeError, match="DistRDF with Dask does not support threaded workers"):
+                Backend.DaskBackend(daskclient=client)
+        finally:
+            client.close()
+            cluster.close()
+
+
 
 class TestInitialization:
     """Check initialization method in the Dask backend"""