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 aedfb48058dc5..cc1d19e4a81ff 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 (totalCnt != 0) {
+    if (other.count != 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 d718ef63b531a..70f9693b4e96b 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
@@ -346,6 +346,23 @@ 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 five rows but
+    // the parallelism is bigger than that. Because the issue was about `AFTAggregator`s
+    // being merged incorrectly when it has an empty partition, the trained model has
+    // 1.0 scale from Euler's number for 0.
+    val points = sc.parallelize(Seq(
+      AFTPoint(Vectors.dense(1.560, -0.605), 1.218, 1.0),
+      AFTPoint(Vectors.dense(0.346, 2.158), 2.949, 0.0),
+      AFTPoint(Vectors.dense(1.380, 0.231), 3.627, 0.0),
+      AFTPoint(Vectors.dense(0.520, 1.151), 0.273, 1.0),
+      AFTPoint(Vectors.dense(0.795, -0.226), 4.199, 0.0)), numSlices = 6)
+    val dataset = sqlContext.createDataFrame(points)
+    val trainer = new AFTSurvivalRegression()
+    val model = trainer.fit(dataset)
+    assert(model.scale != 1)
+  }
 }
 
 object AFTSurvivalRegressionSuite {