The transition toward lower-carbon transport fuels requires energy systems that are not only environmentally advantageous but also technically feasible and economically competitive. Bio-compressed natural gas (Bio-CNG), produced through biogas generation and subsequent upgrading, represents a potential pathway for converting organic waste into a transport fuel while simultaneously creating value from waste streams. This study develops a conceptual techno-economic optimization model for Bio-CNG deployment across South African provinces. The proposed framework integrates feedstock availability, anaerobic digestion, biogas upgrading, compression, transportation infrastructure, vehicle demand, capital expenditure, operating expenditure, and provincial deployment constraints. The methodology is structured as a multi-period, risk-aware optimization problem in which the allocation of Bio-CNG production capacity is determined according to resource availability and economic performance. Particular attention is given to food-waste generation because the conversion of organic waste into biogas provides an opportunity to connect waste-management and transport-energy systems. Previous research has demonstrated significant economic variation among anaerobic digestion, biogas upgrading, and compressed natural gas applications, while South African studies indicate the importance of regional waste and transport characteristics. The resulting model identifies the principal decision variables, constraints, objective functions, and sensitivity parameters governing provincial deployment. The analysis indicates that a phased and geographically differentiated deployment strategy is more appropriate than uniform national expansion. Provinces with higher concentrations of suitable organic feedstocks, transport demand, and infrastructure can potentially support earlier deployment, whereas regions with lower feedstock density may require shared facilities or centralized production hubs. The framework provides a basis for investment prioritization, infrastructure planning, and policy evaluation without assuming that technical feasibility automatically implies economic viability.