diff --git a/pandas/plotting/_matplotlib/timeseries.py b/pandas/plotting/_matplotlib/timeseries.py
index e489b6a5e8f30..c58b42b326c05 100644
--- a/pandas/plotting/_matplotlib/timeseries.py
+++ b/pandas/plotting/_matplotlib/timeseries.py
@@ -251,7 +251,14 @@ def use_dynamic_x(ax: Axes, index: Index) -> bool:
             return index[:1].is_normalized
         period = Period(index[0], freq_str)
         assert isinstance(period, Period)
-        return period.to_timestamp().tz_localize(index.tz) == index[0]
+        period_naive = period.to_timestamp()
+        if index.tz is not None:
+            # Compare naive local times directly
+            tz_naive = index[0].tz_localize(None)  # Strips tz, keeps local time
+            return period_naive == tz_naive
+        else:
+            return period_naive == index[0]
+
     return True
 
 
diff --git a/pandas/tests/plotting/test_series.py b/pandas/tests/plotting/test_series.py
index 779e539b3afba..d32f3e120ef4d 100644
--- a/pandas/tests/plotting/test_series.py
+++ b/pandas/tests/plotting/test_series.py
@@ -1003,3 +1003,18 @@ def test_bar_line_plot(self):
         x_limits = ax.get_xlim()
         assert x_limits[0] <= bar_xticks[0].get_position()[0]
         assert x_limits[1] >= bar_xticks[-1].get_position()[0]
+
+    def test_tseries_plot_dst_transition(self):
+        """
+        Test that plotting tz-aware timeseries works during DST fall-back transition.
+        """
+        # GH62936
+        tind = date_range(
+            "2025-10-26T00:00:00Z",
+            "2025-10-26T03:00:00Z",
+            freq="5min",
+            tz="utc",
+        ).tz_convert("MET")[12:]
+
+        myts = DataFrame({"a": 1}, index=tind)
+        _check_plot_works(myts.plot)