Abstract: Waste electrical and electronic equipment （WEEE） has both resource value and environmental risk characteristics, making its recycling management a key issue in the global circular economy and sustainable development. Although life cycle assessment （LCA） is widely recognized as an effective tool for evaluating the environmental impacts of processes such as WEEE recycling, existing research has largely focused on comparing the environmental impacts of different treatment technologies. There has been little integrated analysis of the systematic interrelationships between management models, technical performance, pathway optimization, and decision-making applications. This review compares and summarizes differences in WEEE recycling management models and systems in various countries and regions. It also systematically examines the environmental impacts of key recycling and treatment technologies, as well as their limiting factors. Furthermore, the challenges faced by LCA in optimizing management pathways and decision-making applications has been discussed. The results suggest that developing countries are significantly behind developed countries in terms of their WEEE recycling management systems, networks, treatment systems, and governance capacity. Current research still faces several key challenges, including discrepancies in accounting boundaries and analytical methods, data quality and regional representativeness, study duration, and the integration of research themes. These issues restrict the gradual expansion of LCA from being used as a single environmental comparison tool to being used as a vital framework that supports multi-dimensional, coordinated decision-making across environmental, economic and social dimensions. Future research should put more emphasis on refining evaluation systems and optimized policy coordination from a life-cycle perspective, particularly focusing on China and other developing countries. Concurrently, efforts should be made to standardize methodologies, develop localized datasets and integrate dynamic evaluation approaches, while strengthening the synergy between the environmental, economic and social dimensions to improve the ability to make comprehensive decisions.