diff --git a/gtsam/hybrid/HybridBayesNet.cpp b/gtsam/hybrid/HybridBayesNet.cpp
index a80c4c0f2..841b74f4f 100644
--- a/gtsam/hybrid/HybridBayesNet.cpp
+++ b/gtsam/hybrid/HybridBayesNet.cpp
@@ -61,12 +61,13 @@ HybridBayesNet HybridBayesNet::prune(size_t maxNrLeaves) const {
     }
   }
 
-  // Prune the joint. NOTE: again, possibly quite expensive.
-  const DiscreteConditional::shared_ptr pruned = joint.prune(maxNrLeaves);
+  // Prune the joint. NOTE: imperative and, again, possibly quite expensive.
+  DiscreteConditional pruned(joint);
+  pruned.prune(maxNrLeaves);
 
   // Create a the result starting with the pruned joint.
   HybridBayesNet result;
-  result.push_back(std::move(pruned));
+  result.push_back(std::make_shared<DiscreteConditional>(pruned));
 
   /* To prune, we visitWith every leaf in the HybridGaussianConditional.
    * For each leaf, using the assignment we can check the discrete decision tree
@@ -80,7 +81,7 @@ HybridBayesNet HybridBayesNet::prune(size_t maxNrLeaves) const {
   for (auto &&conditional : *this) {
     if (auto hgc = conditional->asHybrid()) {
       // Prune the hybrid Gaussian conditional!
-      auto prunedHybridGaussianConditional = hgc->prune(*pruned);
+      auto prunedHybridGaussianConditional = hgc->prune(pruned);
 
       // Type-erase and add to the pruned Bayes Net fragment.
       result.push_back(prunedHybridGaussianConditional);
diff --git a/gtsam/hybrid/HybridBayesTree.cpp b/gtsam/hybrid/HybridBayesTree.cpp
index 65664e2b1..22777600f 100644
--- a/gtsam/hybrid/HybridBayesTree.cpp
+++ b/gtsam/hybrid/HybridBayesTree.cpp
@@ -200,12 +200,11 @@ VectorValues HybridBayesTree::optimize(const DiscreteValues& assignment) const {
 
 /* ************************************************************************* */
 void HybridBayesTree::prune(const size_t maxNrLeaves) {
-  auto discreteProbs =
+  auto prunedDiscreteProbs =
       this->roots_.at(0)->conditional()->asDiscrete<TableDistribution>();
 
-  DiscreteConditional::shared_ptr prunedDiscreteProbs =
-      discreteProbs->prune(maxNrLeaves);
-  discreteProbs->setData(prunedDiscreteProbs);
+  // Imperative pruning
+  prunedDiscreteProbs->prune(maxNrLeaves);
 
   /// Helper struct for pruning the hybrid bayes tree.
   struct HybridPrunerData {