diff --git a/mllib/src/main/scala/org/apache/spark/ml/regression/AFTSurvivalRegression.scala b/mllib/src/main/scala/org/apache/spark/ml/regression/AFTSurvivalRegression.scala
index cc1d19e4a81f..aedfb48058dc 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/regression/AFTSurvivalRegression.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/regression/AFTSurvivalRegression.scala
@@ -496,7 +496,7 @@ private class AFTAggregator(parameters: BDV[Double], fitIntercept: Boolean)
    * @return This AFTAggregator object.
    */
   def merge(other: AFTAggregator): this.type = {
-    if (other.count != 0) {
+    if (totalCnt != 0) {
       totalCnt += other.totalCnt
       lossSum += other.lossSum
 
diff --git a/mllib/src/test/scala/org/apache/spark/ml/regression/AFTSurvivalRegressionSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/regression/AFTSurvivalRegressionSuite.scala
index e452efbc8df9..d718ef63b531 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/regression/AFTSurvivalRegressionSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/regression/AFTSurvivalRegressionSuite.scala
@@ -346,18 +346,6 @@ class AFTSurvivalRegressionSuite
     testEstimatorAndModelReadWrite(aft, datasetMultivariate,
       AFTSurvivalRegressionSuite.allParamSettings, checkModelData)
   }
-
-  test("SPARK-15892: Incorrectly merged AFTAggregator with zero total count") {
-    // This `dataset` will contain an empty partition because it has two rows but
-    // the parallelism is bigger than that. Because the issue was about `AFTAggregator`s
-    // being merged incorrectly when it has an empty partition, running the codes below
-    // should not throw an exception.
-    val dataset = spark.createDataFrame(
-      sc.parallelize(generateAFTInput(
-        1, Array(5.5), Array(0.8), 2, 42, 1.0, 2.0, 2.0), numSlices = 3))
-    val trainer = new AFTSurvivalRegression()
-    trainer.fit(dataset)
-  }
 }
 
 object AFTSurvivalRegressionSuite {