Reverse Logistics (RL) groups the activities involved in the return flows of products at the end of their economic life cycle. Enterprises and policy makers all over the world are currently researching, designing and putting in place strategies to recover and recycle products and raw materials, both for the benefit of the environment and to increase profits. However, the management of return flows is complex and unpredictable because consumer behavior introduces uncertainties in timing, quantity, and quality of the end-of-life products. To proactively cope with these concerns, we propose a metamodel that serves as a foundation for a domain specific modeling language (DSML) to understand RL processes and apply analysis techniques. This DSML can also be used to examine aspects such as RL strategies, capacity of the facilities, and incentives (e.g., sanctions and tax reliefs introduced by regulators). The core element of this approach is an extensible metamodel which can be used for analyzing specific applications of RL such as E-waste management.