Improved scientific tools are a key driver of scientific progress. While computational methods for prediction of hydrogen-bond-acceptor strength were first reported over three decades ago, the broader utilization of these tools has been impeded by the lack of a workflow usable by non-computational scientists. Here, we address this lacuna through the development of a robust and efficient algorithm for pK BHX prediction. Our hydrogen-bond-basicityprediction workflow predicts per-site pK BHX values directly from 2D-or 3D-representations of molecules, with no additional input required, and provides insight into otherwise opaque structural features of lead molecules, as illustrated by examples from the medicinal chemistry literature. We anticipate that this approach will be a valuable addition to the armamentarium of tools available to the modern drug hunter, and hope that this software can be more closely integrated into lead optimization programs in the future.