Backcasting is not a new concept for scientists dealing with carbon mitigation or climate change mitigation issues around the world, but could be an innovative idea for public, local, and national policy planners as they are so far only familiar with forecast scenarios for different issues and sectors. Defining a roadmap to achieving low carbon targets and explaining these targets in quantitative form as much as possible is known as backcasting. Plenty of computer-based quantitative models and tools are used to outline low carbon society scenarios in the Asia-Pacific region and implementations of such models are underway. This paper spotlights these quantitative models and tools which are used to achieve backcasting benchmarks. These models are critically reviewed for their functioning and real possibilities on ground levels and suggestions have been made to improve practical implementation in developing Asia. The study found that all these models are highly acceptable and applicable in Asian countries but actual applications are rare, with Japan as the leading country in implementing such applications, followed by Malaysia. Estimation of CO2 sinks, open availability, and energy service demands (built-in option) are major weaknesses of the models. We also concluded that these computer-based quantitative models are helpful for almost all of the countries of the Asia-Pacific region facing such issues as data limitation, fewer resources, and lack of government participation.