<p>In the energy and carbon management, rising carbon dioxide (CO₂) emissions from the burning of fossil fuels such as oil and natural gas is directly linked to climate change, global warming, and air pollution. Solar-driven CO₂ reduction for producing fuels and chemicals is an important and promising technology to achieve carbon neutrality and sustainable energy. There is an urgent need for a decision support system (DSS) in order to provide actionable insights for policymakers and plan to implement the optimal solar-driven CO₂ reduction technologies. An intelligent DSS based on the Delphi and combined compromise solution (CoCoSo) methods under the linear Diophantine fuzzy set (LDFS) is conducted by considering the sustainability and suitability policies. Five technologies for solar-driven CO₂ reduction consisting of solar-to-methanol, solar-to-methane, photovoltaic-electrochemical CO₂ reduction, photocatalytic CO₂ reduction, and photoelectrochemical CO₂ reduction are considered as decision-making alternatives. The DSS results reveal that the solar-to-methane technology with the value of 2.0399 is the optimal and suitable alternative for Iran’s southern regions in order to promote carbon management, attain climate change mitigation, and help navigate sustainable energy transition by accelerating these types of technologies. This research can be a practical work for policymakers considering insights related to sustainability and suitability principles, solar-driven CO₂ reduction technologies, and the proposed fuzzy optimization model in the uncertainty of the decision-making process.</p> Graphical Abstract <p></p>