diff --git a/x-pack/plugin/ml/qa/native-multi-node-tests/src/test/java/org/elasticsearch/xpack/ml/integration/RegressionIT.java b/x-pack/plugin/ml/qa/native-multi-node-tests/src/test/java/org/elasticsearch/xpack/ml/integration/RegressionIT.java
index fc22edb5d1c..31f70e02547 100644
--- a/x-pack/plugin/ml/qa/native-multi-node-tests/src/test/java/org/elasticsearch/xpack/ml/integration/RegressionIT.java
+++ b/x-pack/plugin/ml/qa/native-multi-node-tests/src/test/java/org/elasticsearch/xpack/ml/integration/RegressionIT.java
@@ -38,13 +38,13 @@ import java.util.Set;
 
 import static org.elasticsearch.test.hamcrest.OptionalMatchers.isPresent;
 import static org.hamcrest.Matchers.anyOf;
-import static org.hamcrest.Matchers.closeTo;
 import static org.hamcrest.Matchers.emptyString;
 import static org.hamcrest.Matchers.equalTo;
 import static org.hamcrest.Matchers.greaterThan;
 import static org.hamcrest.Matchers.hasSize;
 import static org.hamcrest.Matchers.is;
 import static org.hamcrest.Matchers.lessThan;
+import static org.hamcrest.Matchers.lessThanOrEqualTo;
 import static org.hamcrest.Matchers.not;
 
 public class RegressionIT extends MlNativeDataFrameAnalyticsIntegTestCase {
@@ -461,7 +461,6 @@ public class RegressionIT extends MlNativeDataFrameAnalyticsIntegTestCase {
             "Finished analysis");
     }
 
-    @AwaitsFix(bugUrl = "https://github.com/elastic/elasticsearch/issues/60212")
     public void testAliasFields() throws Exception {
         // The goal of this test is to assert alias fields are included in the analytics job.
         // We have a simple dataset with two integer fields: field_1 and field_2.
@@ -528,19 +527,26 @@ public class RegressionIT extends MlNativeDataFrameAnalyticsIntegTestCase {
         startAnalytics(jobId);
         waitUntilAnalyticsIsStopped(jobId);
 
+        double predictionErrorSum = 0.0;
+
         SearchResponse sourceData = client().prepareSearch(sourceIndex).setSize(totalDocCount).get();
         for (SearchHit hit : sourceData.getHits()) {
             Map<String, Object> destDoc = getDestDoc(config, hit);
             Map<String, Object> resultsObject = getMlResultsObjectFromDestDoc(destDoc);
 
-            int featureValue = (int) destDoc.get("field_1");
-            double predictionValue = (double) resultsObject.get(predictionField);
-            assertThat(predictionValue, closeTo(2 * featureValue, 10.0));
-
             assertThat(resultsObject.containsKey(predictionField), is(true));
             assertThat(resultsObject.containsKey("is_training"), is(true));
+
+            int featureValue = (int) destDoc.get("field_1");
+            double predictionValue = (double) resultsObject.get(predictionField);
+            predictionErrorSum += Math.abs(predictionValue - 2 * featureValue);
         }
 
+        // We assert on the mean prediction error in order to reduce the probability
+        // the test fails compared to asserting on the prediction of each individual doc.
+        double meanPredictionError = predictionErrorSum / sourceData.getHits().getHits().length;
+        assertThat(meanPredictionError, lessThanOrEqualTo(10.0));
+
         assertProgressComplete(jobId);
         assertThat(searchStoredProgress(jobId).getHits().getTotalHits().value, equalTo(1L));
         assertModelStatePersisted(stateDocId());