diff --git a/bayesnet/ensembles/BoostAODE.h b/bayesnet/ensembles/BoostAODE.h
index 2c0ed14..6e7b546 100644
--- a/bayesnet/ensembles/BoostAODE.h
+++ b/bayesnet/ensembles/BoostAODE.h
@@ -7,7 +7,7 @@
 namespace bayesnet {
     class BoostAODE : public Ensemble {
     public:
-        BoostAODE(bool predict_voting = true);
+        BoostAODE(bool predict_voting = false);
         virtual ~BoostAODE() = default;
         std::vector<std::string> graph(const std::string& title = "BoostAODE") const override;
         void setHyperparameters(const nlohmann::json& hyperparameters) override;
diff --git a/docs/BoostAODE.md b/docs/BoostAODE.md
index a04cc0e..1279407 100644
--- a/docs/BoostAODE.md
+++ b/docs/BoostAODE.md
@@ -24,7 +24,7 @@ The hyperparameters defined in the algorithm are:
 
   Default value is *-1* so every time any of those algorithms are called, the threshold has to be set to the desired value.
 
-- ***predict_voting*** (*boolean*): Sets whether the algorithm will use *model voting* to predict the result. If set to false, the weighted average of the probabilities of each model's prediction will be used. Default value: *true*.
+- ***predict_voting*** (*boolean*): Sets whether the algorithm will use *model voting* to predict the result. If set to false, the weighted average of the probabilities of each model's prediction will be used. Default value: *false*.
 
 - ***predict_single*** (*boolean*): Sets whether the algorithm will use single-model prediction in the learning process. If set to *false*, all models trained up to that point will be used to calculate the prediction necessary to update the weights in the learning process. Default value: *true*.