The remanufacturing of machine tools is a complex approach to regain the original identity, accuracy, and precision of faulty machine tools in order to save time, money, and natural resources. Despite its great importance, the process is not yet fully standardized, and every industry has its own policy to remanufacture their machine tools. This may be due to the fact that machine tools remanufacturing is a stochastic process and problems are mostly related to decision making, and there is no optimized methodology to deal with such problems. Our research is aimed at finding an optimal strategy for remanufacturing decision making problems to make this process more efficient and sustainable. A case study is presented, and information about a test problem is collected based on machine tools remanufacturing knowledge. Decisions are made and the data is organized in a quality function deployment matrix. Analytical hierarchy process and fuzzy linear regression technique are used to quantify statistical data in order to make QFD more practical. Fuzzy relations among QFD data are calculated, and a weighted distance metric is used to find the best solution. Considering the cost of remanufacturing a fuzzy parameter, separate cost-benefit analysis is done to control the cash flow.