The design and optimization of solar thermal collectors play a crucial role in harnessing renewable energy from the sun, a resource that is both abundant and sustainable. Solar thermal collectors capture solar radiation and convert it into thermal energy. This thermal energy is used for heating water, air, or other fluids in residential, commercial, and industrial applications. As the global demand for clean energy continues to grow, the efficiency and effectiveness of solar thermal collectors have become increasingly important. Artificial intelligence-based machine learning methods (AI-ML) to design and optimize solar thermal collectors involves a multidisciplinary approach that integrates principles of thermodynamics, fluid dynamics, materials science, and energy engineering. This chapter provides the insights, key considerations, and strategies to design and optimize solar thermal collectors.