The global push for a sustainable economy has led to a sharp rise in the demand for minerals, essential for supporting low-carbon and renewable energy technologies. However, the mining industry in Asia faces formidable environmental, technological, and financial hurdles in transitioning to greener operations. This study provides an empirical assessment of mineral prospecting through a carbon-neutral lens, employing the Cross-sectional Autoregressive Distributive Lag (CS-ARDL) econometric model to simulate sustainable mining scenarios. Analyzing annual data from 2015 to 2022, the research uncovers several critical findings. First, while mineral exploration holds significant potential to enable the green transition by supplying vital materials for renewable technologies, current practices are environmentally unsustainable. Second, innovative technologies such as AI and big data can substantially improve the sector's operational efficiency and reduce environmental harm, but adoption remains limited. Third, financial institutions are increasingly imposing stricter sustainability benchmarks, creating new opportunities for green investment but also posing risks for non-compliant firms. Fourth, the study highlights that without stronger community engagement and enhanced social governance, mining projects face social license risks, potentially derailing operations. Overall, the results stress the necessity for a balanced approach, integrating economic viability, environmental protection, and social responsibility, to transition Asia's mining industry toward a greener future. The findings present clear pathways for policy interventions and strategic industry actions to drive sustainable mineral exploration.