Aim: The major issue for many anti-tubercular agents is the resistance of Mycobacterium tuberculosis strains. Quinoline compounds serve as anti-mycobacterial agents with encouraging anti-tubercular activity. The main aim of this study is to develop 2D QSAR models for a series of arylthioquinoline to predict their ideal characteristics as potential anti-tubercular agents. Materials and Methods: Used CS Chem Office 2004 and Molecular Modeling Pro 6.1.0 software for modeling and models development. Some of the statistical parameters were calculated by using QSARINS (HYPERLINK "http:// www.qsar.it/"www.qsar.it). We have used MLR techniques to develop QSAR models. The developed QSAR models were found to be statistically significant based on internal and external validation parameters. Results: The significance and predictive ability of the developed QSAR model was confirmed as it satisfied the following conditions: r 2 =0.817>0.6; CCC tr =0.899>0.85; q 2 LOO=0.729>0.5; pred_r 2 =0.922>0.6; pred_r 2 se=0.186; CCC pred =0.907>0.85; r 2 m=0.753>0.5; r' 2 m=0.714>0.5; ∆ r 2 m=0.039<0.2k'=0.966; k=1.014 (0.85