diff --git a/mllib/src/main/scala/org/apache/spark/mllib/classification/NaiveBayes.scala b/mllib/src/main/scala/org/apache/spark/mllib/classification/NaiveBayes.scala
index 8c8e4a161aa5b..76d2be3c632a3 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/classification/NaiveBayes.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/classification/NaiveBayes.scala
@@ -24,6 +24,7 @@ import org.apache.spark.SparkContext._
 import org.apache.spark.mllib.linalg.{DenseVector, SparseVector, Vector}
 import org.apache.spark.mllib.regression.LabeledPoint
 import org.apache.spark.rdd.RDD
+import scala.collection.mutable
 
 /**
  * Model for Naive Bayes Classifiers.
@@ -65,6 +66,25 @@ class NaiveBayesModel private[mllib] (
   override def predict(testData: Vector): Double = {
     labels(brzArgmax(brzPi + brzTheta * testData.toBreeze))
   }
+
+  def classProbabilities(testData: RDD[Vector]):
+   RDD[scala.collection.Map[Double, Double]] = {
+    val bcModel = testData.context.broadcast(this)
+    testData.mapPartitions { iter =>
+      val model = bcModel.value
+      iter.map(model.classProbabilities)
+    }
+  }
+
+  def classProbabilities(testData: Vector): scala.collection.Map[Double, Double] = {
+    val posteriors = (brzPi + brzTheta * testData.toBreeze) 
+    val sum = posteriors.sum
+    val probs:mutable.Map[Double,Double] = 
+      mutable.Map.empty[Double, Double]
+    posteriors.foreachPair((k,v) => probs += (labels(k) -> v/sum))
+    probs
+  }
+
 }
 
 /**