diff --git a/jvm-packages/xgboost4j-spark/src/main/scala/ml/dmlc/xgboost4j/scala/spark/XGBoostClassifier.scala b/jvm-packages/xgboost4j-spark/src/main/scala/ml/dmlc/xgboost4j/scala/spark/XGBoostClassifier.scala
index 4f3d50f9f06a..85f9b3eaba26 100644
--- a/jvm-packages/xgboost4j-spark/src/main/scala/ml/dmlc/xgboost4j/scala/spark/XGBoostClassifier.scala
+++ b/jvm-packages/xgboost4j-spark/src/main/scala/ml/dmlc/xgboost4j/scala/spark/XGBoostClassifier.scala
@@ -22,6 +22,7 @@ import scala.collection.mutable
 
 import ml.dmlc.xgboost4j.java.Rabit
 import ml.dmlc.xgboost4j.scala.{Booster, DMatrix, XGBoost => SXGBoost}
+import ml.dmlc.xgboost4j.scala.{EvalTrait, ObjectiveTrait}
 import ml.dmlc.xgboost4j.scala.spark.params._
 import ml.dmlc.xgboost4j.{LabeledPoint => XGBLabeledPoint}
 
@@ -134,6 +135,10 @@ class XGBoostClassifier (
 
   def setNumEarlyStoppingRounds(value: Int): this.type = set(numEarlyStoppingRounds, value)
 
+  def setCustomObj(value: ObjectiveTrait): this.type = set(customObj, value)
+
+  def setCustomEval(value: EvalTrait): this.type = set(customEval, value)
+
   // called at the start of fit/train when 'eval_metric' is not defined
   private def setupDefaultEvalMetric(): String = {
     require(isDefined(objective), "Users must set \'objective\' via xgboostParams.")
diff --git a/jvm-packages/xgboost4j-spark/src/main/scala/ml/dmlc/xgboost4j/scala/spark/XGBoostRegressor.scala b/jvm-packages/xgboost4j-spark/src/main/scala/ml/dmlc/xgboost4j/scala/spark/XGBoostRegressor.scala
index 29f289102372..6b6c635bdabf 100644
--- a/jvm-packages/xgboost4j-spark/src/main/scala/ml/dmlc/xgboost4j/scala/spark/XGBoostRegressor.scala
+++ b/jvm-packages/xgboost4j-spark/src/main/scala/ml/dmlc/xgboost4j/scala/spark/XGBoostRegressor.scala
@@ -23,6 +23,7 @@ import ml.dmlc.xgboost4j.java.Rabit
 import ml.dmlc.xgboost4j.{LabeledPoint => XGBLabeledPoint}
 import ml.dmlc.xgboost4j.scala.spark.params.{DefaultXGBoostParamsReader, _}
 import ml.dmlc.xgboost4j.scala.{Booster, DMatrix, XGBoost => SXGBoost}
+import ml.dmlc.xgboost4j.scala.{EvalTrait, ObjectiveTrait}
 
 import org.apache.hadoop.fs.Path
 import org.apache.spark.TaskContext
@@ -136,6 +137,10 @@ class XGBoostRegressor (
 
   def setNumEarlyStoppingRounds(value: Int): this.type = set(numEarlyStoppingRounds, value)
 
+  def setCustomObj(value: ObjectiveTrait): this.type = set(customObj, value)
+
+  def setCustomEval(value: EvalTrait): this.type = set(customEval, value)
+
   // called at the start of fit/train when 'eval_metric' is not defined
   private def setupDefaultEvalMetric(): String = {
     require(isDefined(objective), "Users must set \'objective\' via xgboostParams.")