This chapter investigates the transformative impact of computational modeling and predictive formulation techniques in rigid polyurethane foam (RPUF) research. As both an academic and industrial breakthrough, computational approaches are setting a new standard for foam technology, offering precise optimization, enhanced performance, and substantial improvements in environmental sustainability. Predictive formulation is at the forefront of these changes, guiding the field toward products that meet exacting standards for insulation, structural stability, and sustainable resource use. This chapter expands on the wide-ranging implications of these advancements, from foundational academic research to commercial production, examining how the integration of machine learning and data-driven insights reshapes RPUF development, accelerates product cycles, and sets the stage for innovations that will shape the future of material science.