The increasing demand for sustainable energy storage has driven significant interest in zinc-ion batteries (ZIBs) as a cost-effective and environmentally friendly alternative to lithium-ion batteries (LIBs). In this study, we present a computationally driven approach to accelerate the discovery and design of cathode materials for rechargeable ZIBs, combining data filtering techniques with ab initio simulations. By screening 153 902 inorganic compounds from the Materials Project database, we identify eight promising candidates for cathode materials, among which ZnCrO4, ZnMnO3, and ZnMoO4 exhibit the most favorable electrochemical properties for large-scale applications, and where ZnCrO4 has not been discussed before, neither theoretically nor experimentally. These materials demonstrate minimal volumetric changes (less than 6%) during charge–discharge cycles, high theoretical specific capacities, elevated energy densities, high voltages, and reduced ionic diffusion barriers, all of which are critical for optimizing ZIB performance. Our findings highlight the potential of high-throughput computational screening to accelerate the development of next-generation energy storage materials, providing valuable insights for future experimental validation.