Recently several 1,3,4-oxadiazole derivatives were identified as potentially active antimycobacterial agents. Various 5-aryl-2-thio-1,3,4-oxadiazoles have been reported having good antimycobacterial activity against Mycobacterium tuberculosis H37Rv (ATCC 27294). In this paper we report 3D QSAR studies for the 41 molecules of 1,3,4-oxadiazoles by using k-Nearest Neighbor Molecular Field Analysis (kNN-MFA) combined with various selection procedures. Using kNN-MFA approach 52 3D-QSAR models were generated; one of these models was selected on the basis of q2 and pred_r2 values. The selected Model had shown good internal and external predictivity for the training set of 33 molecules and test set of 8 molecules with validation (q2) and cross validation (pred_r2) values of 0.5022 & 0.2898 respectively. This model can be used for preliminary screening of large diversified compound libraries. The model has shown that presence of sulphur is must for activity; however the larger bulky substituents reduce the activity. The presence of halogen and other non-halogen groups have also contributed to the activity. Hence the future schemes with smaller groups on sulphur and electronegative groups in the molecule would result in potentially active molecules.