Strategies for reuse of components are important in order to create a closed loop manufacturing system. Over decades, the notion has been gaining ground due to environmental and legislative reasons. Reuse of components is desirable and in many cases might be economically beneficial. However, the implementation of reuse strategies has been hindered by the requirement of reliable methodologies to assess the remaining life and reuse potential of used components. The estimation of the remaining life is problematic as the useful life of a component is affected by several causes of obsolescence. The common causes are due to physical and technological issues. So far, little research has attempted to address these issues simultaneously, and integrating them. This thesis seeks to develop methodologies that aid in predicting the integrated remaining lifetime of used components. There are three core parts of this research. First, the methodology determines the remaining life of used components from the physical lifetime perspective. This was derived from the estimation of physical failure using failure rate data, and the statistical analysis of usage intensity age as obtained from customers survey. Second, the research presents the use of the technological forecasting technique to predict the remaining technological life. As it is influenced by the technology progress, the forecast was developed on the basis of product technology clusters and market trend extrapolation analysis. Finally, the resulting estimations from the two aspects were combined to obtain an integrated assessment for estimating the remaining life of components. The potential for components in a product to be reused is justified when the remaining life is greater than the average expected lifespan of the product. Two cases of domestic appliances – televisions and washing machines were used to highlight and demonstrate the validity of the proposed methodology. The results show that the proposed method provides the practitioners with a promising tool for end-of-life decision making. This is in particularly attractive when used as a preliminary decision support tool prior to the time consuming and costly processes such as disassembly and quality testing.