After Alzheimer's disease, Parkinson's disease is the most prevalent neurodegenerative condition. Because it is fatal and affects a large proportion of the world's population over the age of 60, the development of new drugs to treat it is crucial. To achieve this objective, we used the 3D-QSAR technique to design effective hMAO-B inhibitors from a 1-(prop-2-yn-1-ylamino)-2,3-dihydro-1H-indene-4-thiol chain. The 3D-QSAR models were generated by combining comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA). In this study, the different field models obtained proved that the CoMSIA/SEA model is the best model with excellent predictive power over several models (Q² = 0.701; R² = 0.926; R²_test= 0.69). A new group of MAO-B inhibitors was predicted based on this fitting model, and the pharmacokinetic properties were studied using ADMET in silico prediction. All examined compounds showed good oral bioavailability. In addition, the docking simulation of the designed compound M4 and the most active compound of the training set K12 were analyzed. The results showed that the newly designed compound M4 remained more stable at the active site of the receptor compared to the compound K12, and we can finally rely on it as a potential pharmacological compound.