diff --git a/CHANGELOG.md b/CHANGELOG.md
index 0354cf10..96e03b2a 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -1,6 +1,7 @@
 # v0.7.3 (Upcoming)
 
 ### New Checks
+* Added `check_spike_times_without_nans` to detect NaN values in Units spike times, which indicate conversion bugs or unclean array padding. [#689](https://github.com/NeurodataWithoutBorders/nwbinspector/pull/689)
 
 ### Improvements
 * Raised the minimum required PyNWB to `>=4.0` to track the latest PyNWB release. [#708](https://github.com/NeurodataWithoutBorders/nwbinspector/pull/708)
diff --git a/docs/best_practices/ecephys.rst b/docs/best_practices/ecephys.rst
index 9af1e9cf..1a3989e3 100644
--- a/docs/best_practices/ecephys.rst
+++ b/docs/best_practices/ecephys.rst
@@ -151,6 +151,19 @@ Check function: :py:meth:`~nwbinspector.checks._ecephys.check_spike_times_not_in
 
 
 
+.. _best_practice_spike_times_without_nans:
+
+No NaN Spike Times
+~~~~~~~~~~~~~~~~~~
+
+Spike times are physical event timestamps and must always be valid floating-point numbers. A NaN value in the
+``spike_times`` column typically indicates a conversion bug or array padding that was not cleaned up before writing
+to NWB. Unlike missing data in continuous signals, a spike either occurred at a specific time or it did not, so
+NaN is never meaningful. Clean your spike time arrays to remove any NaN values before adding them to the Units table.
+
+Check function: :py:meth:`~nwbinspector.checks._ecephys.check_spike_times_without_nans`
+
+
 .. _best_practice_ascending_spike_times:
 
 Ascending Spike Times
diff --git a/src/nwbinspector/checks/__init__.py b/src/nwbinspector/checks/__init__.py
index c01ad2ab..2bf3777a 100644
--- a/src/nwbinspector/checks/__init__.py
+++ b/src/nwbinspector/checks/__init__.py
@@ -14,6 +14,7 @@
     check_negative_spike_times,
     check_spike_times_not_in_samples,
     check_spike_times_not_in_unobserved_interval,
+    check_spike_times_without_nans,
     check_units_resolution_is_set,
     check_units_resolution_is_valid,
     check_units_table_duration,
@@ -186,6 +187,7 @@
     "check_spatial_series_degrees_magnitude",
     "check_spatial_series_unit",
     "check_ascending_spike_times",
+    "check_spike_times_without_nans",
     "check_electrical_series_unscaled_data",
     "check_units_resolution_is_valid",
     "check_units_resolution_is_set",
diff --git a/src/nwbinspector/checks/_ecephys.py b/src/nwbinspector/checks/_ecephys.py
index dd28edc5..da5eaf6b 100644
--- a/src/nwbinspector/checks/_ecephys.py
+++ b/src/nwbinspector/checks/_ecephys.py
@@ -244,6 +244,23 @@ def check_spike_times_not_in_unobserved_interval(units_table: Units, nunits: int
     return None
 
 
+@register_check(importance=Importance.CRITICAL, neurodata_type=Units)
+def check_spike_times_without_nans(units_table: Units) -> Optional[InspectorMessage]:
+    """
+    Check if the Units table contains NaN values in spike times.
+
+    Best Practice: :ref:`best_practice_spike_times_without_nans`
+    """
+    if "spike_times" not in units_table:
+        return None
+
+    if np.any(np.isnan(np.asarray(units_table["spike_times"].target.data[:]))):
+        return InspectorMessage(
+            message="Units table contains NaN spike times. Spike times should be valid timestamps in seconds."
+        )
+    return None
+
+
 @register_check(importance=Importance.CRITICAL, neurodata_type=Units)
 def check_ascending_spike_times(units_table: Units, nelems: Optional[int] = NELEMS) -> Optional[InspectorMessage]:
     """
diff --git a/tests/unit_tests/test_ecephys.py b/tests/unit_tests/test_ecephys.py
index f331ed9c..c2bf4037 100644
--- a/tests/unit_tests/test_ecephys.py
+++ b/tests/unit_tests/test_ecephys.py
@@ -20,6 +20,7 @@
     check_negative_spike_times,
     check_spike_times_not_in_samples,
     check_spike_times_not_in_unobserved_interval,
+    check_spike_times_without_nans,
     check_units_resolution_is_set,
     check_units_resolution_is_valid,
     check_units_table_duration,
@@ -437,6 +438,30 @@ def test_check_spike_times_not_in_unobserved_interval_multiple_units():
     )
 
 
+class TestCheckSpikeTimesWithoutNans(TestCase):
+    def setUp(self):
+        self.units_table = Units()
+
+    def test_spike_times_without_nans_valid(self):
+        self.units_table.add_unit(spike_times=[0.0, 0.1, 0.2])
+        self.units_table.add_unit(spike_times=[1.0, 1.1, 1.2])
+        assert check_spike_times_without_nans(units_table=self.units_table) is None
+
+    def test_spike_times_with_nans(self):
+        self.units_table.add_unit(spike_times=[0.0, np.nan, 0.2])
+        assert check_spike_times_without_nans(units_table=self.units_table) == InspectorMessage(
+            message="Units table contains NaN spike times. Spike times should be valid timestamps in seconds.",
+            importance=Importance.CRITICAL,
+            check_function_name="check_spike_times_without_nans",
+            object_type="Units",
+            object_name="Units",
+            location="/",
+        )
+
+    def test_spike_times_without_nans_empty(self):
+        assert check_spike_times_without_nans(units_table=self.units_table) is None
+
+
 class TestCheckAscendingSpikeTimes(TestCase):
     def setUp(self):
         self.units_table = Units()