diff --git a/R/pkg/vignettes/sparkr-vignettes.Rmd b/R/pkg/vignettes/sparkr-vignettes.Rmd
index d4713de7806a..68a18ab57b28 100644
--- a/R/pkg/vignettes/sparkr-vignettes.Rmd
+++ b/R/pkg/vignettes/sparkr-vignettes.Rmd
@@ -590,6 +590,7 @@ summary(model)
 Predict values on training data
 ```{r}
 prediction <- predict(model, training)
+head(select(prediction, "Class", "Sex", "Age", "Freq", "Survived", "prediction"))
 ```
 
 #### Logistic Regression
@@ -613,6 +614,7 @@ summary(model)
 Predict values on training data
 ```{r}
 fitted <- predict(model, training)
+head(select(fitted, "Class", "Sex", "Age", "Freq", "Survived", "prediction"))
 ```
 
 Multinomial logistic regression against three classes
@@ -807,6 +809,7 @@ df <- createDataFrame(t)
 dtModel <- spark.decisionTree(df, Survived ~ ., type = "classification", maxDepth = 2)
 summary(dtModel)
 predictions <- predict(dtModel, df)
+head(select(predictions, "Class", "Sex", "Age", "Freq", "Survived", "prediction"))
 ```
 
 #### Gradient-Boosted Trees
@@ -822,6 +825,7 @@ df <- createDataFrame(t)
 gbtModel <- spark.gbt(df, Survived ~ ., type = "classification", maxDepth = 2, maxIter = 2)
 summary(gbtModel)
 predictions <- predict(gbtModel, df)
+head(select(predictions, "Class", "Sex", "Age", "Freq", "Survived", "prediction"))
 ```
 
 #### Random Forest
@@ -837,6 +841,7 @@ df <- createDataFrame(t)
 rfModel <- spark.randomForest(df, Survived ~ ., type = "classification", maxDepth = 2, numTrees = 2)
 summary(rfModel)
 predictions <- predict(rfModel, df)
+head(select(predictions, "Class", "Sex", "Age", "Freq", "Survived", "prediction"))
 ```
 
 #### Bisecting k-Means