diff --git a/google/cloud/aiplatform/pipeline_jobs.py b/google/cloud/aiplatform/pipeline_jobs.py
index 8bf06ccb49..84b39c2ae8 100644
--- a/google/cloud/aiplatform/pipeline_jobs.py
+++ b/google/cloud/aiplatform/pipeline_jobs.py
@@ -264,7 +264,7 @@ def state(self) -> Optional[gca_pipeline_state_v1beta1.PipelineState]:
     @property
     def _has_run(self) -> bool:
         """Helper property to check if this pipeline job has been run."""
-        return bool(self._gca_resource.name)
+        return bool(self._gca_resource.create_time)
 
     @property
     def has_failed(self) -> bool:
@@ -310,3 +310,19 @@ def _block_until_complete(self):
                 log_wait = min(log_wait * multiplier, max_wait)
                 previous_time = current_time
             time.sleep(wait)
+
+    def cancel(self) -> None:
+        """Starts asynchronous cancellation on the PipelineJob. The server
+        makes a best effort to cancel the job, but success is not guaranteed.
+        On successful cancellation, the PipelineJob is not deleted; instead it
+        becomes a job with state set to `CANCELLED`.
+
+        Raises:
+            RuntimeError: If this PipelineJob has not started running.
+        """
+        if not self._has_run:
+            raise RuntimeError(
+                "This PipelineJob has not been launched, use the `run()` method "
+                "to start. `cancel()` can only be called on a job that is running."
+            )
+        self.api_client.cancel_pipeline_job(name=self.resource_name)
diff --git a/tests/unit/aiplatform/test_pipeline_jobs.py b/tests/unit/aiplatform/test_pipeline_jobs.py
index e156163348..18dc692d38 100644
--- a/tests/unit/aiplatform/test_pipeline_jobs.py
+++ b/tests/unit/aiplatform/test_pipeline_jobs.py
@@ -21,12 +21,11 @@
 from unittest import mock
 from importlib import reload
 from unittest.mock import patch
+from datetime import datetime
 
 from google.auth import credentials as auth_credentials
-
 from google.cloud import aiplatform
 from google.cloud import storage
-
 from google.cloud.aiplatform import pipeline_jobs
 from google.cloud.aiplatform import initializer
 from google.protobuf import json_format
@@ -72,6 +71,7 @@
 _TEST_PIPELINE_RESOURCE_NAME = (
     f"{_TEST_PARENT}/fakePipelineJobs/{_TEST_PIPELINE_JOB_ID}"
 )
+_TEST_PIPELINE_CREATE_TIME = datetime.now()
 
 
 @pytest.fixture
@@ -82,13 +82,16 @@ def mock_pipeline_service_create():
         mock_create_pipeline_job.return_value = gca_pipeline_job_v1beta1.PipelineJob(
             name=_TEST_PIPELINE_JOB_NAME,
             state=gca_pipeline_state_v1beta1.PipelineState.PIPELINE_STATE_SUCCEEDED,
+            create_time=_TEST_PIPELINE_CREATE_TIME,
         )
         yield mock_create_pipeline_job
 
 
 def make_pipeline_job(state):
     return gca_pipeline_job_v1beta1.PipelineJob(
-        name=_TEST_PIPELINE_JOB_NAME, state=state,
+        name=_TEST_PIPELINE_JOB_NAME,
+        state=state,
+        create_time=_TEST_PIPELINE_CREATE_TIME,
     )
 
 
@@ -130,6 +133,14 @@ def mock_pipeline_service_get():
         yield mock_get_pipeline_job
 
 
+@pytest.fixture
+def mock_pipeline_service_cancel():
+    with mock.patch.object(
+        pipeline_service_client_v1beta1.PipelineServiceClient, "cancel_pipeline_job"
+    ) as mock_cancel_pipeline_job:
+        yield mock_cancel_pipeline_job
+
+
 @pytest.fixture
 def mock_load_json():
     with patch.object(storage.Blob, "download_as_bytes") as mock_load_json:
@@ -155,13 +166,10 @@ def setup_method(self):
     def teardown_method(self):
         initializer.global_pool.shutdown(wait=True)
 
+    @pytest.mark.usefixtures("mock_load_json")
     @pytest.mark.parametrize("sync", [True, False])
     def test_run_call_pipeline_service_create(
-        self,
-        mock_pipeline_service_create,
-        mock_pipeline_service_get,
-        mock_load_json,
-        sync,
+        self, mock_pipeline_service_create, mock_pipeline_service_get, sync,
     ):
         aiplatform.init(
             project=_TEST_PROJECT,
@@ -213,3 +221,51 @@ def test_run_call_pipeline_service_create(
         assert job._gca_resource == make_pipeline_job(
             gca_pipeline_state_v1beta1.PipelineState.PIPELINE_STATE_SUCCEEDED
         )
+
+    @pytest.mark.usefixtures(
+        "mock_pipeline_service_create", "mock_pipeline_service_get", "mock_load_json",
+    )
+    def test_cancel_pipeline_job(
+        self, mock_pipeline_service_cancel,
+    ):
+        aiplatform.init(
+            project=_TEST_PROJECT,
+            staging_bucket=_TEST_GCS_BUCKET_NAME,
+            credentials=_TEST_CREDENTIALS,
+        )
+
+        job = pipeline_jobs.PipelineJob(
+            display_name=_TEST_PIPELINE_JOB_ID,
+            template_path=_TEST_TEMPLATE_PATH,
+            job_id=_TEST_PIPELINE_JOB_ID,
+        )
+
+        job.run()
+        job.cancel()
+
+        mock_pipeline_service_cancel.assert_called_once_with(
+            name=_TEST_PIPELINE_JOB_NAME
+        )
+
+    @pytest.mark.usefixtures(
+        "mock_pipeline_service_create", "mock_pipeline_service_get", "mock_load_json",
+    )
+    def test_cancel_pipeline_job_without_running(
+        self, mock_pipeline_service_cancel,
+    ):
+        aiplatform.init(
+            project=_TEST_PROJECT,
+            staging_bucket=_TEST_GCS_BUCKET_NAME,
+            credentials=_TEST_CREDENTIALS,
+        )
+
+        job = pipeline_jobs.PipelineJob(
+            display_name=_TEST_PIPELINE_JOB_ID,
+            template_path=_TEST_TEMPLATE_PATH,
+            job_id=_TEST_PIPELINE_JOB_ID,
+        )
+
+        with pytest.raises(RuntimeError) as e:
+            job.cancel()
+
+        assert e.match(regexp=r"PipelineJob has not been launched")