diff --git a/ci/code_checks.sh b/ci/code_checks.sh
index f2d9f582d8932..443753aa175fd 100755
--- a/ci/code_checks.sh
+++ b/ci/code_checks.sh
@@ -164,7 +164,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
         -i "pandas.core.groupby.SeriesGroupBy.plot PR02" \
         -i "pandas.core.groupby.SeriesGroupBy.sem SA01" \
         -i "pandas.core.resample.Resampler.__iter__ RT03,SA01" \
-        -i "pandas.core.resample.Resampler.ffill RT03" \
         -i "pandas.core.resample.Resampler.get_group RT03,SA01" \
         -i "pandas.core.resample.Resampler.groups SA01" \
         -i "pandas.core.resample.Resampler.indices SA01" \
diff --git a/pandas/core/resample.py b/pandas/core/resample.py
index b621fcf9a6415..711396096a5e3 100644
--- a/pandas/core/resample.py
+++ b/pandas/core/resample.py
@@ -529,6 +529,11 @@ def ffill(self, limit: int | None = None):
         """
         Forward fill the values.
 
+        This method fills missing values by propagating the last valid
+        observation forward, up to the next valid observation. It is commonly
+        used in time series analysis when resampling data to a higher frequency
+        (upsampling) and filling gaps in the resampled output.
+
         Parameters
         ----------
         limit : int, optional
@@ -536,7 +541,8 @@ def ffill(self, limit: int | None = None):
 
         Returns
         -------
-        An upsampled Series.
+        Series
+            The resampled data with missing values filled forward.
 
         See Also
         --------