Determining the aggregation propensity of protein-based biotherapeutics is an important step in the drug development process. Typically, a great deal of data collected over a large period of time is needed to estimate the aggregation propensity of biotherapeutics. Thus, candidates cannot be screened early on for aggregation propensity, but early screening is desirable to help streamline drug development. Here, we present a simple molecular computational method to predict the aggregation propensity via hydrophobic interactions, thought to be the most common mechanism of aggregation, and electrostatic interactions. This method uses a new quantity termed Developability Index. It is a function of an antibody's net charge, calculated on the full-length antibody structure, and the spatial aggregation propensity, calculated on the complementarity-determining region structure. Its accuracy is due to the molecular level details and the incorporation of the tertiary structure of the antibody. It is particularly applicable to antibodies or other proteins for which structures are available or could be determined accurately using homology modeling. Applications include the selection of molecules in the discovery or early development process, selection of mutants for stability, and estimation of resources needed for development of a given biomolecule.