Reverse logistics (RL) is considered the reverse manner of gathering and redeploying goods at the end of their lifetime span from consumers to manufacturers in order to reutilize, dispose, or remanufacture. Whereas RL has many economic benefits, it presents compromises to businesses that wish to remain competitive but be responsible global citizens in terms of social, environmental, risk, and safety aspects of sustainable development. Managing RL systems therefore is considered a multifaceted mission that necessities a significant level of technology, infrastructure, experience, and competence. Consequently, various commerce institutions are looking to outsourcing their RL actions to third-party reverse logistics providers (3PRLPs). In this work, a novel hybrid multiple-criteria decision-making (MCDM) framework is proposed to classify and choose 3PRLPs, which comprises the analytic hierarchy process (AHP) technique, and technique for order of preference by similarity to ideal solution (TOPSIS) technique under neutrosophic environment. Accordingly, AHP is availed for defining weights of key dimensions and their subindices. In addition, TOPSIS was adopted for ranking the specified 3PRLPs. The efficiency of the proposed approach is clarified through application on a considered car parts manufacturing industry case in Egypt, which shows the features of the combined MCDM methods. A comparative and sensitivity analyses were performed to highlight the benefits of the incorporated MCDM methods and for clarifying the effect of changing weights in selecting the sustainable 3PRLP alternative, respectively. The suggested framework is also shown to present more functional execution when dealing with uncertainties and qualitative inputs, demonstrating applicability to a broad range of applications. Ultimately, the best sustainable 3PRLPs were selected and results show that social, environmental, and risk and safety sustainability factors have the greatest influence when determining 3PRLPs alternatives