diff --git a/gtsam/hybrid/HybridBayesNet.cpp b/gtsam/hybrid/HybridBayesNet.cpp
index 0db1b0c48..3b5ab5b80 100644
--- a/gtsam/hybrid/HybridBayesNet.cpp
+++ b/gtsam/hybrid/HybridBayesNet.cpp
@@ -38,21 +38,17 @@ bool HybridBayesNet::equals(const This &bn, double tol) const {
 }
 
 /* ************************************************************************* */
-DecisionTreeFactor::shared_ptr HybridBayesNet::discreteConditionals() const {
-  AlgebraicDecisionTree<Key> discreteProbs;
-
+DiscreteConditional::shared_ptr HybridBayesNet::discreteConditionals() const {
   // The canonical decision tree factor which will get
   // the discrete conditionals added to it.
-  DecisionTreeFactor discreteProbsFactor;
+  DiscreteConditional discreteProbs;
 
   for (auto &&conditional : *this) {
     if (conditional->isDiscrete()) {
-      // Convert to a DecisionTreeFactor and add it to the main factor.
-      DecisionTreeFactor f(*conditional->asDiscrete());
-      discreteProbsFactor = discreteProbsFactor * f;
+      discreteProbs = discreteProbs * (*conditional->asDiscrete());
     }
   }
-  return std::make_shared<DecisionTreeFactor>(discreteProbsFactor);
+  return std::make_shared<DiscreteConditional>(discreteProbs);
 }
 
 /* ************************************************************************* */
@@ -146,8 +142,8 @@ std::function<double(const Assignment<Key> &, double)> prunerFunc(
 /* ************************************************************************* */
 void HybridBayesNet::updateDiscreteConditionals(
     const DecisionTreeFactor &prunedDiscreteProbs) {
-  //TODO(Varun) Should prune the joint conditional, maybe during elimination?
-  // Loop with index since we need it later.
+  // TODO(Varun) Should prune the joint conditional, maybe during elimination?
+  //  Loop with index since we need it later.
   for (size_t i = 0; i < this->size(); i++) {
     HybridConditional::shared_ptr conditional = this->at(i);
     if (conditional->isDiscrete()) {
@@ -179,7 +175,7 @@ void HybridBayesNet::updateDiscreteConditionals(
 HybridBayesNet HybridBayesNet::prune(size_t maxNrLeaves) {
   // Get the decision tree of only the discrete keys
   gttic_(HybridBayesNet_PruneDiscreteConditionals);
-  DecisionTreeFactor::shared_ptr discreteConditionals =
+  DiscreteConditional::shared_ptr discreteConditionals =
       this->discreteConditionals();
   const DecisionTreeFactor prunedDiscreteProbs =
       discreteConditionals->prune(maxNrLeaves);
diff --git a/gtsam/hybrid/HybridBayesNet.h b/gtsam/hybrid/HybridBayesNet.h
index 23fc4d5d3..19e88d754 100644
--- a/gtsam/hybrid/HybridBayesNet.h
+++ b/gtsam/hybrid/HybridBayesNet.h
@@ -139,9 +139,9 @@ class GTSAM_EXPORT HybridBayesNet : public BayesNet<HybridConditional> {
   /**
    * @brief Get all the discrete conditionals as a decision tree factor.
    *
-   * @return DecisionTreeFactor::shared_ptr
+   * @return DiscreteConditional::shared_ptr
    */
-  DecisionTreeFactor::shared_ptr discreteConditionals() const;
+  DiscreteConditional::shared_ptr discreteConditionals() const;
 
   /**
    * @brief Sample from an incomplete BayesNet, given missing variables.