diff --git a/gtsam/hybrid/HybridGaussianConditional.cpp b/gtsam/hybrid/HybridGaussianConditional.cpp
index 478f94f18..1c3a69ce7 100644
--- a/gtsam/hybrid/HybridGaussianConditional.cpp
+++ b/gtsam/hybrid/HybridGaussianConditional.cpp
@@ -337,24 +337,6 @@ HybridGaussianConditional::shared_ptr HybridGaussianConditional::prune(
                                                      pruned_conditionals);
 }
 
-/* *******************************************************************************/
-AlgebraicDecisionTree<Key> HybridGaussianConditional::logProbability(
-    const VectorValues &continuousValues) const {
-  // functor to calculate (double) logProbability value from
-  // GaussianConditional.
-  auto probFunc =
-      [continuousValues](const GaussianConditional::shared_ptr &conditional) {
-        if (conditional) {
-          return conditional->logProbability(continuousValues);
-        } else {
-          // Return arbitrarily small logProbability if conditional is null
-          // Conditional is null if it is pruned out.
-          return -1e20;
-        }
-      };
-  return DecisionTree<Key, double>(conditionals_, probFunc);
-}
-
 /* *******************************************************************************/
 double HybridGaussianConditional::logProbability(
     const HybridValues &values) const {
diff --git a/gtsam/hybrid/HybridGaussianConditional.h b/gtsam/hybrid/HybridGaussianConditional.h
index 8f3aa6778..f3bf4d839 100644
--- a/gtsam/hybrid/HybridGaussianConditional.h
+++ b/gtsam/hybrid/HybridGaussianConditional.h
@@ -194,16 +194,6 @@ class GTSAM_EXPORT HybridGaussianConditional
   /// Getter for the underlying Conditionals DecisionTree
   const Conditionals &conditionals() const;
 
-  /**
-   * @brief Compute logProbability of the HybridGaussianConditional as a tree.
-   *
-   * @param continuousValues The continuous VectorValues.
-   * @return AlgebraicDecisionTree<Key> A decision tree with the same keys
-   * as the conditionals, and leaf values as the logProbability.
-   */
-  AlgebraicDecisionTree<Key> logProbability(
-      const VectorValues &continuousValues) const;
-
   /**
    * @brief Compute the logProbability of this hybrid Gaussian conditional.
    *
diff --git a/gtsam/hybrid/tests/testHybridGaussianConditional.cpp b/gtsam/hybrid/tests/testHybridGaussianConditional.cpp
index 803d42f03..24eb409a1 100644
--- a/gtsam/hybrid/tests/testHybridGaussianConditional.cpp
+++ b/gtsam/hybrid/tests/testHybridGaussianConditional.cpp
@@ -74,17 +74,6 @@ TEST(HybridGaussianConditional, Invariants) {
 /// Check LogProbability.
 TEST(HybridGaussianConditional, LogProbability) {
   using namespace equal_constants;
-  auto actual = hybrid_conditional.logProbability(vv);
-
-  // Check result.
-  std::vector<DiscreteKey> discrete_keys = {mode};
-  std::vector<double> leaves = {conditionals[0]->logProbability(vv),
-                                conditionals[1]->logProbability(vv)};
-  AlgebraicDecisionTree<Key> expected(discrete_keys, leaves);
-
-  EXPECT(assert_equal(expected, actual, 1e-6));
-
-  // Check for non-tree version.
   for (size_t mode : {0, 1}) {
     const HybridValues hv{vv, {{M(0), mode}}};
     EXPECT_DOUBLES_EQUAL(conditionals[mode]->logProbability(vv),