A consensus model was built by combining the predictions of the best models derived from Morgan and RDK fingerprints (Morgan::SVM and RDK::SVM), also supported on the fact that predictions between models relying on the same fingerprint are more closely related than those relying on different representations as demonstrated by the hierarchical clustering analysis of their cross-validated predictions. The consensus models' performance and the two source models were analyzed on a DM basis, categorizing the predictions according to the Jaccard distance of the compounds in the test set to those in the training set. For the single target binary classification, the consensus model showed a significantly higher precision for identifying active compounds than those obtained by the individual models regardless of the DM. This trend was preserved when the models were evaluated to predict epigenetic targets.