diff --git a/domain/epc_prediction/comparable_properties.py b/domain/epc_prediction/comparable_properties.py
index 47b762346..3e111bb36 100644
--- a/domain/epc_prediction/comparable_properties.py
+++ b/domain/epc_prediction/comparable_properties.py
@@ -22,8 +22,25 @@ from domain.geospatial.coordinates import Coordinates
 _DEFAULT_MINIMUM_COHORT = 5
 
 # Half-width of the floor-area conditioning band: an expired Historic EPC's
-# observed floor area keeps comparables within ±5% of it (ADR-0054).
-_FLOOR_AREA_TOLERANCE = 0.05
+# observed floor area keeps comparables within ±20% of it — a coarse
+# dwelling-size filter, not a precision match. Evidence (ADR-0054 amendment,
+# 439-pair harness): the historic TFA agrees with the newly lodged one within
+# ±5% only 45% of the time (remeasurement + extensions) but within ±20% 82%.
+FLOOR_AREA_TOLERANCE = 0.20
+
+# RdSAP Table S1 band letters in chronological order, for band-distance checks.
+_AGE_BAND_ORDER = "ABCDEFGHIJKLM"
+
+
+def age_bands_within_one(candidate: object, target_band: object) -> bool:
+    """Whether two Table S1 band letters are at most one band apart. Assessors
+    re-band constantly (harness: 52% exact agreement historic-vs-new, 90%
+    within one band), so the age filter keeps the band NEIGHBOURHOOD."""
+    if not (isinstance(candidate, str) and isinstance(target_band, str)):
+        return False
+    if candidate not in _AGE_BAND_ORDER or target_band not in _AGE_BAND_ORDER:
+        return False
+    return abs(_AGE_BAND_ORDER.index(candidate) - _AGE_BAND_ORDER.index(target_band)) <= 1
 
 
 @dataclass(frozen=True)
@@ -94,7 +111,9 @@ def select_comparables(
     )
     cohort = _maybe_filter(
         cohort,
-        lambda c: _main_construction_age_band(c) == target.construction_age_band,
+        lambda c: age_bands_within_one(
+            _main_construction_age_band(c), target.construction_age_band
+        ),
         active=target.construction_age_band is not None,
         minimum_cohort=minimum_cohort,
     )
@@ -109,7 +128,7 @@ def select_comparables(
         cohort,
         lambda c: target_area is not None
         and abs(c.epc.total_floor_area_m2 - target_area)
-        <= _FLOOR_AREA_TOLERANCE * target_area,
+        <= FLOOR_AREA_TOLERANCE * target_area,
         active=target_area is not None,
         minimum_cohort=minimum_cohort,
     )
diff --git a/scripts/expired_prediction_pairs_harness.py b/scripts/expired_prediction_pairs_harness.py
index bcab7a4da..267e4092a 100644
--- a/scripts/expired_prediction_pairs_harness.py
+++ b/scripts/expired_prediction_pairs_harness.py
@@ -43,7 +43,9 @@ sys.path.insert(0, str(Path(__file__).resolve().parents[1]))
 from datatypes.epc.domain.epc_property_data import EpcPropertyData  # noqa: E402
 from datatypes.epc.domain.historic_epc import HistoricEpc  # noqa: E402
 from domain.epc_prediction.comparable_properties import (  # noqa: E402
+    FLOOR_AREA_TOLERANCE,
     ComparableProperty,
+    age_bands_within_one,
     select_comparables,
 )
 from domain.epc_prediction.epc_prediction import EpcPrediction  # noqa: E402
@@ -226,7 +228,7 @@ def _actual_fuel(epc: EpcPropertyData) -> Optional[object]:
 def _tfa_within_band(actual_tfa: float, hist_tfa: Optional[float]) -> Optional[bool]:
     if hist_tfa is None:
         return None
-    return abs(actual_tfa - hist_tfa) <= 0.05 * hist_tfa
+    return abs(actual_tfa - hist_tfa) <= FLOOR_AREA_TOLERANCE * hist_tfa
 
 
 @dataclass(frozen=True)
@@ -267,7 +269,7 @@ def simulate_conditioning_ladder(
     apply(
         "construction_age_band",
         age_band is not None,
-        [c for c in cohort if _actual_age_band(c.epc) == age_band],
+        [c for c in cohort if age_bands_within_one(_actual_age_band(c.epc), age_band)],
     )
     apply(
         "main_fuel",
@@ -282,7 +284,7 @@ def simulate_conditioning_ladder(
             for c in cohort
             if total_floor_area_m2 is not None
             and abs(c.epc.total_floor_area_m2 - total_floor_area_m2)
-            <= 0.05 * total_floor_area_m2
+            <= FLOOR_AREA_TOLERANCE * total_floor_area_m2
         ],
     )
     return steps
@@ -321,7 +323,7 @@ def format_diagnosis(rows: list[dict[str, object]]) -> str:
         "wall_construction",
         "construction_age_band",
         "main_fuel",
-        "tfa_within_5pct",
+        "tfa_within_band",
     )
     lines += [
         "",