Digital twinning of any business process creates opportunities for integrating life cycle thinking to enhance the environmental sustainability of a supply chain with real-time monitoring and control through informed, timely decisions. This is made possible as a digital twin facilitates continuous data acquisition, visualization, and performs analytics including simulation modelling, machine learning, optimization and dynamic Life Cycle Assessment. This research presents the design and development of a decision support framework that applies life cycle thinking to guide the adaptation of digital twining for sustainable supply chain management. The proposed framework capitalizes on the ISO framework on digital twins (ISO 23247 Series) and expands towards upstream, core process and downstream activities of supply chains. It further incorporates simulation, data analytics and Life Cycle Impact Assessment aspects to facilitate decision support at strategic, tactical and operations levels, thereby contributing to the framework’s uniqueness.