India’s urban infrastructure financing problem is usually framed as a shortage of debt, grants, budgetary transfers or private investment. This paper approaches the issue from a different public finance perspective by examining land value capture as a nonconventional but institutionally relevant financing mechanism for Indian cities. Land value capture is based on the principle that when public investment in infrastructure increases private land and property values, a part of the publicly created and privately appropriated gain may be recovered by the public authority and reinvested in urban infrastructure. Metro rail corridors provide a particularly suitable setting for such an analysis because station accessibility can alter land values, redevelopment incentives, commercial intensity and municipal revenue potential within defined influence zones. Focusing on the post 2017 policy context in India, after the adoption of the Value Capture Finance Policy Framework, National Transit Oriented Development Policy and Metro Rail Policy, this paper develops an evidence based methodological framework for estimating land value gains around metro corridors. The proposed design uses a quasi-experimental difference-indifferences and event study approach to compare property value and municipal revenue changes in station influence zones with comparable non-station areas before and after metro opening. The article does not provide unsubstantiated estimates. Instead, it specifies the required variables, spatial units, treatment control structure, empirical equations, identification assumptions, robustness checks and policy translation logic. It claims that land value capture cannot be seen as an arbitrary extra tax but rather as a proportional recovery of quantifiable publicly created value. The paper concludes that Indian cities need an evidence based land value capture model where charges are pegged on the observed land value gains, backed by GIS based valuation systems, clear revenue utilization and equity protection of tenants, small businesses and low income households.