diff --git a/mltrail_verifiable_provenance_ledger_for/__init__.py b/mltrail_verifiable_provenance_ledger_for/__init__.py
index c2d4481..8d5ead0 100644
--- a/mltrail_verifiable_provenance_ledger_for/__init__.py
+++ b/mltrail_verifiable_provenance_ledger_for/__init__.py
@@ -20,6 +20,7 @@ from .adapters import MLFlowAdapter, WandBAdapter, Adapter
 from .registry import ContractRegistry
 from .util import environment_hash
 from .governance import DID, GovernanceLogEntry
+from .reprobundle import ReproBundle
 
 __all__ = [
     "Ledger",
@@ -39,4 +40,5 @@ __all__ = [
     "environment_hash",
     "DID",
     "GovernanceLogEntry",
+    "ReproBundle",
 ]
diff --git a/mltrail_verifiable_provenance_ledger_for/reprobundle.py b/mltrail_verifiable_provenance_ledger_for/reprobundle.py
new file mode 100644
index 0000000..0760be8
--- /dev/null
+++ b/mltrail_verifiable_provenance_ledger_for/reprobundle.py
@@ -0,0 +1,43 @@
+from dataclasses import dataclass, asdict
+from typing import List, Dict, Any, Optional
+import json
+import hashlib
+
+from .contracts import Environment
+
+
+@dataclass
+class ReproBundle:
+    """A compact, content-addressed snapshot describing everything needed to
+    deterministically replay a run (code commit, environment, dataset refs,
+    model ref, and a minimal run manifest).
+
+    This is intentionally small and deterministic so it can be cheaply
+    exchanged between peers and used to compute Merkle-like bundle hashes.
+    """
+    code_commit: str
+    environment: Environment
+    dataset_refs: List[Dict[str, Any]]
+    model_ref: Dict[str, Any]
+    run_manifest: Dict[str, Any]
+    container_hash: Optional[str] = None
+
+    def to_dict(self) -> Dict[str, Any]:
+        # Convert to a canonical dict suitable for hashing/serialization.
+        return {
+            "code_commit": self.code_commit,
+            "environment": self.environment.to_dict(),
+            "container_hash": self.container_hash,
+            "dataset_refs": sorted(self.dataset_refs, key=lambda d: d.get("id") or ""),
+            "model_ref": self.model_ref,
+            "run_manifest": self.run_manifest,
+        }
+
+    def compute_bundle_hash(self) -> str:
+        """Compute a deterministic SHA-256 digest over the canonical bundle
+        representation. Uses JSON with sorted keys so identical bundles always
+        produce the same digest.
+        """
+        payload = self.to_dict()
+        serialized = json.dumps(payload, sort_keys=True, default=str).encode("utf-8")
+        return hashlib.sha256(serialized).hexdigest()
diff --git a/tests/test_reprobundle.py b/tests/test_reprobundle.py
new file mode 100644
index 0000000..c014d5c
--- /dev/null
+++ b/tests/test_reprobundle.py
@@ -0,0 +1,54 @@
+from mltrail_verifiable_provenance_ledger_for.reprobundle import ReproBundle
+from mltrail_verifiable_provenance_ledger_for.contracts import Environment
+
+
+def make_sample_environment():
+    return Environment(
+        id="env1",
+        language="python",
+        version="3.9",
+        dependencies={"numpy": "1.24.0", "pandas": "1.5.3"},
+        container_hash=None,
+    )
+
+
+def test_bundle_hash_deterministic():
+    env = make_sample_environment()
+    bundle1 = ReproBundle(
+        code_commit="deadbeef",
+        environment=env,
+        dataset_refs=[{"id": "ds1", "fingerprint": "fp1"}],
+        model_ref={"id": "m1", "fingerprint": "mf1"},
+        run_manifest={"seed": 42, "cmd": "python train.py"},
+    )
+    bundle2 = ReproBundle(
+        code_commit="deadbeef",
+        environment=make_sample_environment(),
+        dataset_refs=[{"id": "ds1", "fingerprint": "fp1"}],
+        model_ref={"id": "m1", "fingerprint": "mf1"},
+        run_manifest={"seed": 42, "cmd": "python train.py"},
+    )
+
+    h1 = bundle1.compute_bundle_hash()
+    h2 = bundle2.compute_bundle_hash()
+    assert h1 == h2
+
+
+def test_bundle_hash_changes_on_difference():
+    env = make_sample_environment()
+    base = ReproBundle(
+        code_commit="deadbeef",
+        environment=env,
+        dataset_refs=[{"id": "ds1", "fingerprint": "fp1"}],
+        model_ref={"id": "m1", "fingerprint": "mf1"},
+        run_manifest={"seed": 42, "cmd": "python train.py"},
+    )
+    modified = ReproBundle(
+        code_commit="cafebabe",  # different commit
+        environment=env,
+        dataset_refs=[{"id": "ds1", "fingerprint": "fp1"}],
+        model_ref={"id": "m1", "fingerprint": "mf1"},
+        run_manifest={"seed": 42, "cmd": "python train.py"},
+    )
+
+    assert base.compute_bundle_hash() != modified.compute_bundle_hash()