diff --git a/DESCRIPTION b/DESCRIPTION
index a745e819f..74f62fa96 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,6 +1,6 @@
 Package: parsnip
 Title: A Common API to Modeling and Analysis Functions
-Version: 1.3.3.9000
+Version: 1.3.3.9001
 Authors@R: c(
     person("Max", "Kuhn", , "max@posit.co", role = c("aut", "cre")),
     person("Davis", "Vaughan", , "davis@posit.co", role = "aut"),
diff --git a/NEWS.md b/NEWS.md
index 234821fc7..b77bd424e 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -1,5 +1,7 @@
 # parsnip (development version)
 
+* Fixes issue with running predictions for Decision Trees in Spark (#1309)
+
 * Updates to some boosting tuning parameter information: (#1306)
   - lightgbm and catboost have smaller default ranges for the learning rate: -3 to -1 / 2 in log10 units.
   - lightgbm, xgboost, catboost, and C5.0 have smaller default ranges for the sampling proportion: 0.5 to 1.0.
diff --git a/R/decision_tree_data.R b/R/decision_tree_data.R
index 533a714c8..d53263f2c 100644
--- a/R/decision_tree_data.R
+++ b/R/decision_tree_data.R
@@ -325,7 +325,7 @@ set_pred(
     pre = NULL,
     post = format_spark_num,
     func = c(pkg = "sparklyr", fun = "ml_predict"),
-    args = list(object = quote(object$fit), dataset = quote(new_data))
+    args = list(x = quote(object$fit), dataset = quote(new_data))
   )
 )
 
@@ -338,7 +338,7 @@ set_pred(
     pre = NULL,
     post = format_spark_class,
     func = c(pkg = "sparklyr", fun = "ml_predict"),
-    args = list(object = quote(object$fit), dataset = quote(new_data))
+    args = list(x = quote(object$fit), dataset = quote(new_data))
   )
 )
 
@@ -351,6 +351,6 @@ set_pred(
     pre = NULL,
     post = format_spark_probs,
     func = c(pkg = "sparklyr", fun = "ml_predict"),
-    args = list(object = quote(object$fit), dataset = quote(new_data))
+    args = list(x = quote(object$fit), dataset = quote(new_data))
   )
 )