Engineering project management has entered a transformative phase where digitalization, process optimization, and sustainability imperatives converge to redefine cost and value delivery. Traditional project evaluation methods, often focused on initial capital costs, fail to capture the broader economic, operational, and environmental implications over an asset’s entire life cycle. This gap underscores the need for an integrated life-cycle cost-benefit evaluation framework that holistically incorporates Building Information Modeling (BIM), Lean construction practices, and sustainability principles. At the broader level, BIM enables advanced visualization, data-driven decision-making, and predictive modeling across design, construction, and operations, ensuring stakeholders anticipate risks and optimize resource allocation. Lean practices, on the other hand, minimize waste, streamline workflows, and enhance productivity, leading to measurable reductions in cost overruns and project delays. When sustainability is embedded as a core dimension, the framework extends beyond financial considerations to encompass environmental performance, energy efficiency, and social responsibility, aligning engineering projects with global carbon reduction and resilience goals. This integration creates a synergistic evaluation model where life-cycle costs are assessed against tangible and intangible benefits, enabling project managers to justify investments not only on economic efficiency but also on long-term stakeholder value. Furthermore, the proposed approach strengthens project governance by providing transparent metrics that support client satisfaction, regulatory compliance, and sustainable competitive advantage. By narrowing the scope to engineering project management, the study demonstrates how integrating BIM, Lean, and sustainability into a unified cost-benefit evaluation methodology bridges the divide between short-term efficiency and long-term value creation. This holistic perspective positions project managers to make informed, future-ready decisions in increasingly complex engineering environments.