diff --git a/domain/modelling/plan.py b/domain/modelling/plan.py
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+++ b/domain/modelling/plan.py
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+"""Plan and Plan Measure — the Modelling stage's persisted output (ADR-0017).
+
+A **Plan** is the per-Property output of one Scenario's modelling run: the
+selected **Optimised Package** (its **Plan Measures**) plus the Property's
+post-retrofit figures. It is single-phase — multi-phase is deferred
+(ADR-0005) — so the headline figures are flat on the Plan.
+
+A **Plan Measure** is the *output* counterpart of a Recommendation's candidate
+Option: the one Option the Optimiser kept, frozen with its installed **Cost**
+and its final-package (role-3) attributed **impact**. See CONTEXT.md.
+"""
+
+from dataclasses import dataclass
+
+from datatypes.epc.domain.epc import Epc
+from domain.modelling.package_scorer import Score
+from domain.modelling.recommendation import Cost
+from domain.modelling.scoring import MeasureImpact
+
+
+@dataclass(frozen=True)
+class PlanMeasure:
+    """One selected Measure Option as it lands in a Plan: the measure, its
+    installed Cost, and its role-3 (final-package cascade) attributed impact."""
+
+    measure_type: str
+    description: str
+    cost: Cost
+    impact: MeasureImpact
+
+
+@dataclass(frozen=True)
+class Plan:
+    """A Property's Plan for one Scenario: the selected Plan Measures and the
+    baseline / post-retrofit whole-package Scores. The persisted headline
+    figures are derived from these (cost aggregates, CO₂ saving, post band)."""
+
+    measures: tuple[PlanMeasure, ...]
+    baseline: Score
+    post_retrofit: Score
+
+    @property
+    def cost_of_works(self) -> float:
+        """Sum of the Plan Measures' fully-loaded Costs."""
+        return sum((measure.cost.total for measure in self.measures), 0.0)
+
+    @property
+    def contingency_cost(self) -> float:
+        """Sum of each Plan Measure's contingency (its Cost total × its
+        per-Measure-Type contingency rate)."""
+        return sum(
+            (
+                measure.cost.total * measure.cost.contingency_rate
+                for measure in self.measures
+            ),
+            0.0,
+        )
+
+    @property
+    def post_sap_continuous(self) -> float:
+        """The whole-package re-score's un-rounded SAP rating."""
+        return self.post_retrofit.sap_continuous
+
+    @property
+    def post_epc_rating(self) -> Epc:
+        """The post-retrofit EPC band, from the rounded SAP rating."""
+        return Epc.from_sap_score(round(self.post_retrofit.sap_continuous))
+
+    @property
+    def co2_savings_kg_per_yr(self) -> float:
+        """Whole-package CO₂ reduction (kg/yr) vs the baseline re-score. The
+        persistence mapper converts to tonnes for the live column contract."""
+        return self.baseline.co2_kg_per_yr - self.post_retrofit.co2_kg_per_yr
diff --git a/tests/domain/modelling/test_plan.py b/tests/domain/modelling/test_plan.py
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+++ b/tests/domain/modelling/test_plan.py
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+"""Behaviour of the Plan / PlanMeasure domain types: the per-Property output
+of one Scenario's modelling run. A Plan carries its selected Plan Measures
+(the Optimised Package) plus the baseline/post-retrofit Scores, and derives
+the persisted headline figures (cost aggregates, CO₂ saving, post-retrofit
+band). Single-phase, flat post-retrofit figures (ADR-0005 / ADR-0017).
+"""
+
+from __future__ import annotations
+
+from datatypes.epc.domain.epc import Epc
+from domain.modelling.package_scorer import Score
+from domain.modelling.plan import Plan, PlanMeasure
+from domain.modelling.recommendation import Cost
+from domain.modelling.scoring import MeasureImpact
+
+
+def _measure(measure_type: str, total: float, rate: float) -> PlanMeasure:
+    return PlanMeasure(
+        measure_type=measure_type,
+        description=measure_type.replace("_", " "),
+        cost=Cost(total=total, contingency_rate=rate),
+        impact=MeasureImpact(
+            sap_points=1.0, co2_savings_kg_per_yr=1.0, energy_savings_kwh_per_yr=1.0
+        ),
+    )
+
+
+def test_plan_aggregates_cost_and_savings_and_bands_the_post_sap() -> None:
+    # Arrange
+    measures: tuple[PlanMeasure, ...] = (
+        _measure("cavity_wall_insulation", total=1000.0, rate=0.10),
+        _measure("loft_insulation", total=500.0, rate=0.20),
+    )
+    baseline = Score(
+        sap_continuous=40.0, co2_kg_per_yr=4000.0, primary_energy_kwh_per_yr=20000.0
+    )
+    post = Score(
+        sap_continuous=70.4, co2_kg_per_yr=3600.0, primary_energy_kwh_per_yr=18000.0
+    )
+    plan = Plan(measures=measures, baseline=baseline, post_retrofit=post)
+
+    # Act / Assert
+    assert abs(plan.cost_of_works - 1500.0) <= 1e-9
+    assert abs(plan.contingency_cost - 200.0) <= 1e-9  # 1000*0.10 + 500*0.20
+    assert abs(plan.co2_savings_kg_per_yr - 400.0) <= 1e-9  # baseline - post
+    assert abs(plan.post_sap_continuous - 70.4) <= 1e-9
+    assert plan.post_epc_rating is Epc.C  # round(70.4) = 70 → band C (69–80)