his thesis introduces a Model Predictive Fuzzy Control (MPFC) framework for mission-planning in multi-agent systems operating in dynamic, uncertain environments. MPFC integrates predictive decision-making from Model Predictive Control (MPC) with the adaptability of Fuzzy Logic Control (FLC) to handle complex, time-sensitive tasks. A generic mathematical formulation is developed and applied to a multi-agent Search and Rescue case study with fire and wind dynamics. Comparative performance analysis against MPC and Pre-Tuned FLC controllers, along with sensitivity analyses and design exploration, demonstrate that MPFC can outperform existing approaches and maintain robust performance under varying conditions. Although this technique is promising, several limitations and challenges are identified, suggesting avenues for future research to refine and enhance its applicability.