diff --git a/realestate-lab/app/matcher.py b/realestate-lab/app/matcher.py
index 3df8b2b..60039b8 100644
--- a/realestate-lab/app/matcher.py
+++ b/realestate-lab/app/matcher.py
@@ -6,12 +6,13 @@ from .db import _conn, _profile_row_to_dict
 
 logger = logging.getLogger("realestate-lab")
 
-TIER_WEIGHTS = {"S": 1.00, "A": 0.80, "B": 0.60, "C": 0.40, "D": 0.20}
+TIER_POINTS = {"S": 25, "A": 20, "B": 15, "C": 10, "D": 5}
 
 
 def _region_score(profile: Dict[str, Any], ann: Dict[str, Any]) -> tuple[int, list[str]]:
-    """지역 점수 계산. 광역 10점 + 자치구 5티어 가중치 0~25점.
-    자치구 기준 미설정 시 광역 매칭만으로 35점 풀 점수(기존 호환).
+    """지역 점수 계산. 광역 10점 + 자치구 5티어 점수 0~25점.
+    preferred_districts에 자치구가 하나라도 등록되면 티어 가중 모드로 동작.
+    자치구가 하나도 등록되지 않으면(빈 dict 또는 모든 티어가 빈 리스트) 광역 매칭만으로 35점 풀 점수(기존 호환).
     """
     region_name = ann.get("region_name") or ""
     district = ann.get("district") or ""
@@ -22,15 +23,14 @@ def _region_score(profile: Dict[str, Any], ann: Dict[str, Any]) -> tuple[int, li
     if not region_match:
         return 0, []
 
-    has_districts = any(preferred_districts.get(t) for t in TIER_WEIGHTS)
+    has_districts = any(preferred_districts.values())
     if not has_districts:
         return 35, [f"선호 지역 일치: {region_name}"]
 
     score = 10
     reasons = [f"광역 일치: {region_name}"]
-    for tier, weight in TIER_WEIGHTS.items():
+    for tier, tier_score in TIER_POINTS.items():
         if district and district in (preferred_districts.get(tier) or []):
-            tier_score = round(25 * weight)
             score += tier_score
             reasons.append(f"자치구 {tier}티어: {district} (+{tier_score})")
             break
diff --git a/realestate-lab/tests/test_matcher.py b/realestate-lab/tests/test_matcher.py
index c757c64..f6bd7b9 100644
--- a/realestate-lab/tests/test_matcher.py
+++ b/realestate-lab/tests/test_matcher.py
@@ -81,3 +81,27 @@ def test_eligibility_score_two_types_returns_20():
 def test_eligibility_score_caps_at_25():
     from app.matcher import _eligibility_score
     assert _eligibility_score(["a", "b", "c", "d", "e"]) == 25
+
+
+def test_region_score_b_tier_district():
+    """광역 매칭 + B티어 자치구: 10 + 15 = 25."""
+    from app.matcher import _region_score
+    profile = {
+        "preferred_regions": ["서울"],
+        "preferred_districts": {"S": [], "A": [], "B": ["관악구"], "C": [], "D": []},
+    }
+    ann = {"region_name": "서울특별시", "district": "관악구"}
+    score, _ = _region_score(profile, ann)
+    assert score == 25
+
+
+def test_region_score_c_tier_district():
+    """광역 매칭 + C티어 자치구: 10 + 10 = 20."""
+    from app.matcher import _region_score
+    profile = {
+        "preferred_regions": ["서울"],
+        "preferred_districts": {"S": [], "A": [], "B": [], "C": ["은평구"], "D": []},
+    }
+    ann = {"region_name": "서울특별시", "district": "은평구"}
+    score, _ = _region_score(profile, ann)
+    assert score == 20