Tuberculosis (TB) continues to be a major global health concern caused by Mycobacterium tuberculosis. The InhA enzyme, a key component in the fatty acid synthesis pathway, plays a crucial role in the production of mycolic acids—essential constituents of the bacterial cell wall. Inhibition of this enzyme is an established mechanism of action for the anti-tubercular drug isoniazid. The present study aims to design and analyze pharmacophore models of isoniazid and its analogues targeting the InhA enzyme using computational tools. Pharmacophore modeling helps identify the essential structural and chemical features responsible for biological activity, such as hydrogen bond donors, hydrogen bond acceptors, hydrophobic centers, and aromatic rings. A series of isoniazid analogues were retrieved from chemical databases, and pharmacophore models were generated and optimized using PharmaGist and Discovery Studio Visualizer. The resulting pharmacophore hypotheses were validated based on fit scores and used for virtual screening through ZINCPharmer to identify new potential hits. The study successfully identified key pharmacophoric features responsible for InhA inhibition and proposed several promising compounds for further docking and biological evaluation. This computational approach demonstrates the effectiveness of pharmacophore modeling in accelerating anti-tubercular drug discovery and optimizing existing leads.