Modern antenna performance is inextricably connected to the characteristics of the materials used to make them. This chapter offers a thorough analysis of material composition optimization for antenna performance, examining the interactions between manufacturing methods, design parameters, and material attributes. Important antenna behavior-influencing parameters, including conductivity, dielectric constant, and loss tangent, are investigated in the framework of multi-objective optimization, aiming for gain, bandwidth, efficiency, and compactness. Materials selection and structural parameters are systematically discussed through the use of computational techniques such as the finite element method (FEM), finite-difference time-domain (FDTD), and advanced optimization algorithms like genetic algorithms (GA), particle swarm optimization (PSO), and artificial neural networks (ANN). The integration of experimental validation techniques, such as impedance measurements and vector network analysis, guarantees simulation correctness and real-world dependability. More sophisticated fabrication techniques that enable complex, lightweight, and high-performance antennas are covered in the chapter, including additive manufacturing, gradient materials, and nanomaterial integration. The focus is on eco-friendly, recyclable materials and the trade-offs between performance, economic viability, and environmental impact. Sustainability and cost issues are also covered. The final section highlights new developments that will revolutionize antenna systems in the future, such as AI-driven optimization and intelligent, adaptable materials. In order to create effective, adaptable, and sustainable antennas that can satisfy the changing needs of IoT, 5G, satellite, and radar applications, this study shows that a comprehensive, material-centric optimization framework is necessary.