Hard-to-abate industrial sectors, including cement, steel, chemical, and refinery industries, account for approximately 25% of global energy consumption and around 20% of total CO₂ emissions. Integrating Carbon Capture and Storage/Utilization (CCS/CCU) systems offers a promising pathway to decarbonize these sectors. However, the transformation of energy and industry presents significant integration challenges, particularly in the context of rapidly evolving environmental conditions and technologies. This study introduces a Prospective Life Cycle Optimization (pLCO) framework that addresses these dynamic changes in both background and foreground systems to model and evaluate CCS/CCU networks for hard-to-abate sectors, focusing on the cement and chemical industries in Europe. The framework optimizes integration designs across a range of scenarios from 2025 to 2050. The optimization problem is formulated as a multi-objective mixed-integer linear programming (MILP) model, balancing environmental metrics assessed through prospective life cycle assessment (pLCA) and total levelized production costs evaluated via prospective techno-economic assessment (pTEA). To tackle uncertainties in prospective system integration, a two-stage stochastic optimization approach is employed, considering factors such as emissions, carbon pricing, production costs, CO₂ storage capacities, and product pricing uncertainties. This framework serves as a critical tool for governments and businesses to identify Pareto-optimal decision strategies under diverse economic and environmental policies. It provides a comprehensive evaluation of the integration potential of emerging CCS/CCU technologies across various countries and regions over long-term periods, supporting the development of sustainable industrial futures through informed decision-making.