Computer-aided drug design approaches were applied to identify chalcones with antiplasmodial activity. The virtual screening was performed as follows: structural standardization of in-house database of chalcones; identification of potential protein targets for the chalcones; homology modeling of the predicted targets; molecular docking studies; and experimental validation. Using these models, we prioritized 16 chalcones with potential antiplasmodial activity, for further experimental evaluation. Among them, LabMol-86 and LabMol-87 showed potent antiplasmodial activity against , while LabMol-63 and LabMol-73 were potent inhibitors of progression into mosquito stages. Our results encourage the exploration of chalcones in hit-to-lead optimization studies for tackling malaria.