Cannabis sativa contains >120 phytocannabinoids, but our understanding of these compounds is limited. Determining the molecular modes of action of the phytocannabinoids may assist in their therapeutic development. Ligand-based virtual screening was used to suggest novel protein targets for phytocannabinoids. The similarity ensemble approach, a virtual screening tool, was applied to target identification for the phytocannabinoids as a class and predicted a possible interaction with the lactate dehydrogenase (LDH) family of enzymes. In order to evaluate this in silico prediction, a panel of 18 phytocannabinoids was screened against two LDH isozymes (LDHA and LDHB) in vitro. Cannabichromene (CBC) and Δ9-tetrahydrocannabinolic acid (Δ9-THCA) inhibited LDHA via a noncompetitive mode of inhibition with respect to pyruvate, with Ki values of 8.5 and 6.5 μM, respectively. In silico modeling was then used to predict the binding site for CBC and Δ9-THCA. Both were proposed to bind within the nicotinamide pocket, overlapping the binding site of the cofactor NADH, which is consistent with the noncompetitive modes of inhibition. Stemming from our in silico screen, CBC and Δ9-THCA were identified as inhibitors of LDHA, a novel molecular target that may contribute to their therapeutic effects.