<p>Material intensive supply chains exert immense pressures on the environment due to unsustainable resource extraction and production methods. This is especially the case in the textile industry due to its reliance on raw materials such as cotton, which demands large amounts of land and water for its production. In this study, we develop an applied Multi-Criteria-Decision-Making (MCDM) framework that incorporates such environmental impacts in its decision-making algorithm, in addition to traditional considerations such as material quality and cost, to help stakeholders determine balanced solutions. The framework is based upon the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and the environmental impacts are calculated using Life Cycle Assessment (LCA). We then demonstrate the utility of this approach by taking the case of recycled yarn production in Bangladesh and identifying optimal yarn options under differing stakeholder priorities and potential future scenarios. We identify several recycled yarn options that outperform yarns based entirely on virgin cotton, thus showcasing how sustainable decisions can be made even in the face of competing material quality and economic concerns. The implications of this approach for decision-makers include robust decision making, flexible data input architecture, and consistency under dynamic scenarios, as well as a modular system that can be iteratively improved in the face of new information and improved methods.</p>