The Monte Carlo method was used for quantitative structure-activity relationships modeling of 36 quinoline/isoquinoline derivatives acting as dipeptidyl peptidase-4 inhibitors. Quantitative structure-activity relationships models were calculated with the representation of the molecular structure by the simplified molecular input-line entry system with one random split into the training and the test set. The statistical quality of the developed model was good. The best calculated quantitative structure-activity relationships model had the following statistical parameters: r(2) = 0.9573 for the training set and r(2) = 0.9079 for the test set. Structural indicators defined as molecular fragments responsible for increases and decreases in the inhibition activity were calculated. The computer-aided design of new compounds as potential dipeptidyl peptidase-4 inhibitors with the application of defined structural alerts was presented.