This chapter introduces a Sustainable Multi-choice Stochastic Multi-objective Multi-item Solid Transportation Problem aimed at balancing economic efficiency and environmental sustainability. The model addresses uncertainties by integrating multi-choice objective function coefficients and constraints with normally distributed random variables. Newton’s divided difference method is utilized to develop an interpolating polynomial for handling multi-choice parameters, while stochastic programming transforms probabilistic constraints into deterministic ones. A hybrid solution method is applied to identify a balanced compromise between conflicting objectives. By incorporating sustainability metrics such as carbon emissions, energy consumption, and resource optimization, the model provides a comprehensive framework for multi-item transportation systems. Numerical examples validate its practicality and demonstrate effectiveness in managing trade-off, contributing to sustainable supply chain optimization.