diff --git a/imap_processing/glows/l2/glows_l2.py b/imap_processing/glows/l2/glows_l2.py
index 29aa589d0..041bf1582 100644
--- a/imap_processing/glows/l2/glows_l2.py
+++ b/imap_processing/glows/l2/glows_l2.py
@@ -1,6 +1,7 @@
 """Module for GLOWS Level 2 processing."""
 
 import dataclasses
+import logging
 
 import numpy as np
 import xarray as xr
@@ -13,6 +14,8 @@
 from imap_processing.glows.l2.glows_l2_data import HistogramL2
 from imap_processing.spice.time import et_to_datetime64, ttj2000ns_to_et
 
+logger = logging.getLogger(__name__)
+
 
 def glows_l2(
     input_dataset: xr.Dataset,
@@ -47,8 +50,11 @@ def glows_l2(
     )
 
     l2 = HistogramL2(input_dataset, pipeline_settings)
-
-    return [create_l2_dataset(l2, cdf_attrs)]
+    if l2.number_of_good_l1b_inputs == 0:
+        logger.warning("No good data found in L1B dataset. Returning empty list.")
+        return []
+    else:
+        return [create_l2_dataset(l2, cdf_attrs)]
 
 
 def create_l2_dataset(
diff --git a/imap_processing/glows/l2/glows_l2_data.py b/imap_processing/glows/l2/glows_l2_data.py
index 52a7510b3..bbed51984 100644
--- a/imap_processing/glows/l2/glows_l2_data.py
+++ b/imap_processing/glows/l2/glows_l2_data.py
@@ -228,13 +228,13 @@ def __init__(self, l1b_dataset: xr.Dataset, pipeline_settings: PipelineSettings)
         good_data = l1b_dataset.isel(
             epoch=self.return_good_times(l1b_dataset["flags"], active_flags)
         )
-        # todo: bad angle filter
-        # TODO filter bad bins out. Needs to happen here while everything is still
-        # per-timestamp.
+        # TODO: bad angle filter
+        # TODO: filter bad bins out. Needs to happen here while everything is still
+        #       per-timestamp.
 
         self.daily_lightcurve = DailyLightcurve(good_data)
 
-        self.total_l1b_inputs = len(good_data["epoch"])
+        self.total_l1b_inputs = len(l1b_dataset["epoch"])
         self.number_of_good_l1b_inputs = len(good_data["epoch"])
         self.identifier = -1  # TODO: retrieve from spin table
         # TODO fill this in
@@ -372,7 +372,7 @@ def return_good_times(flags: xr.DataArray, active_flags: NDArray) -> NDArray:
             An array of indices for good times.
         """
         if len(active_flags) != flags.shape[1]:
-            print("Active flags don't matched expected length")
+            print("Active flags don't match expected length")
 
         # A good time is where all the active flags are equal to one.
         # Here, we mask the active indices using active_flags, and then return the times
diff --git a/imap_processing/tests/glows/test_glows_l2.py b/imap_processing/tests/glows/test_glows_l2.py
index d4df5fda3..a20b4cc96 100644
--- a/imap_processing/tests/glows/test_glows_l2.py
+++ b/imap_processing/tests/glows/test_glows_l2.py
@@ -44,6 +44,7 @@ def test_glows_l2(
     mock_ancillary_exclusions,
     mock_pipeline_settings,
     mock_conversion_table_dict,
+    caplog,
 ):
     mock_spice_function.side_effect = mock_update_spice_parameters
 
@@ -56,11 +57,19 @@ def test_glows_l2(
         mock_pipeline_settings,
         mock_conversion_table_dict,
     )
+
+    # Test case 1: L1B dataset has good times
     l2 = glows_l2(l1b_hist_dataset, mock_pipeline_settings)[0]
     assert l2.attrs["Logical_source"] == "imap_glows_l2_hist"
-
     assert np.allclose(l2["filter_temperature_average"].values, [57.6], rtol=0.1)
 
+    # Test case 2: L1B dataset has no good times (all flags 0)
+    l1b_hist_dataset["flags"].values = np.zeros(l1b_hist_dataset.flags.shape)
+    caplog.set_level("WARNING")
+    result = glows_l2(l1b_hist_dataset, mock_pipeline_settings)
+    assert result == []
+    assert any(record.levelname == "WARNING" for record in caplog.records)
+
 
 @patch.object(HistogramL1B, "flag_uv_source", return_value=np.zeros(3600, dtype=bool))
 @patch.object(HistogramL1B, "update_spice_parameters", autospec=True)
@@ -87,6 +96,8 @@ def test_generate_l2(
     pipeline_settings = PipelineSettings(
         mock_pipeline_settings.sel(epoch=day, method="nearest")
     )
+
+    # Test case 1: L1B dataset has good times
     l2 = HistogramL2(l1b_hist_dataset, pipeline_settings)
 
     expected_values = {
@@ -113,6 +124,12 @@ def test_generate_l2(
         l2.hv_voltage_std_dev, expected_values["hv_voltage_std_dev"], 0.01
     )
 
+    # Test case 2: L1B dataset has no good times (all flags 0)
+    l1b_hist_dataset["flags"].values = np.zeros(l1b_hist_dataset.flags.shape)
+    ds = HistogramL2(l1b_hist_dataset, pipeline_settings)
+    expected_number_of_good_l1b_inputs = 0
+    assert ds.number_of_good_l1b_inputs == expected_number_of_good_l1b_inputs
+
 
 def test_bin_exclusions(l1b_hists):
     # TODO test excluding bins as well