Bahrain is on a mission to cut its carbon emissions by 30% by 2035, and a big part of that is getting more electric vehicles (EVs) on the road. But without enough places to charge these EVs, people won’t buy them, and without enough EVs, investors (including the ministry of Sustainable development) will not build the charging stations. This paper presents a mathematical optimization framework for the deployment of EV charging infrastructure across Bahrain, designed to support the nation’s 2035 carbon reduction targets. By integrating mathematical approaches including linear programming, graph theory, and queuing theory, we will figure out the best places for EV charging stations as well as accessibility, cost effectiveness, energy optimization and waiting time. Our model shows that placing 190 charging points at seven key spots, we could support up to 240,000 EVs by 2035. This would cut-off about 108,000 tons of CO₂ every year, which is a serious dent in Bahrain’s goal to reduce carbon emissions. This model aligns with multiple Sustainable Development Goals (SDGs), particularly SDG 7 (Affordable and Clean Energy), SDG 9 (Industry, Innovation and Infrastructure), and SDG 13 (Climate Action). Our research provides policymakers with a data-driven approach to infrastructure planning that balances economic feasibility with environmental impact, offering a replicable methodology for Gulf Cooperation Council nations pursuing sustainable transportation transitions.