Diabetes accounts for high mortality rate worldwide affecting million of lives annually. Global prevalence of diabetes and its rising frequency makes it a key area of research in drug discovery programs. The research article describes the development of quantitative structure activity relationship model against PPARγ, a promising drug target for diabetes. Multiple linear regression approach was adopted for statistical model development and the QSAR relationship suggested the regression coefficient (r2) of 0.84 and the cross validation coefficient (rCV2) of 0.77. Further, the study suggested that chemical descriptors viz., dipole moment, electron affinity, dielectric energy, secondary amine group count and LogP correlated well with the activity. The docking studies showed that most active gymnemic acid analogues viz., gymnemasin D and gymnemic acid VII possess higher binding affinity to PPARγ. QSAR and ADMET studies based other predicted active gymnemc acid analogues were gymnemic acid I, gymnemic acid II, gymnemic acid III, gymnemic acid VIII, gymnemic acid X, gymnemic acid XII, gymnemic acid XIV, gymnemic acid XVIII and gymnemoside W2. Predicted activity results of three query compounds were found comparable to experimental in vivo data. Oral bioavailability of these active analogues is still a limiting factor and therefore further lead optimization required. Also, such study would be of great help in active pharmacophore discovery and lead optimization, and offering new insights into therapeutics for diabetes mellitus.