The remanufacturing of machinery is a process of disassembly, where parts are inspected, repaired, reconditioned or replaced, recertified, and then reassembled to “like-new” condition. In the modern manufacturing industry, remanufacturing offers the advantages of sustainable energy development, cost savings, and pollution reduction, among other benefits. Assessment of the remaining useful life (RUL) of machinery is key for remanufacturing to determining what components can be shut down and when for off-line remanufacturing. Hence, the accuracy of RUL online assessment is critical to remanufacturing industry practice. This chapter first discusses the concept and technology of remanufacturing and then summarizes the modeling of online RUL assessment, with both physical and data-driven models, comparing the advantages and disadvantages of each technique. Also discussed are two new specific methods in remaining life assessment widely cited in the literature: support vector machine (SVM) method and state-space method (SSM). Two case studies of machine tooling are illustrated in detail, using examples and data from real industry applications to demonstrate RUL assessment. The chapter ends by raising, deliberating, and dispelling some practical concerns with online sensing data modeling and RUL assessment.