Under growing consumer awareness and increasing legislation, firms are realizing the importance of including sustainability within their strategic objectives to promote their green image, enhance their corporate citizenship status, and also improve profit margins. Towards this end, sustainability through product remanufacturing is gaining momentum. However, a key complication for maintaining operational efficiencies during production planning and control of remanufacturing lies in the inability to accurately forecast core returns. These difficulties are mostly attributable to limited visibility and higher levels of uncertainty in reverse logistics. Despite significant advances in the remanufacturing literature over the last two decades, there is not yet a practical approach for modelling core return delay durations when the company is engaged in business with a large remanufacturing product catalog and many customer facilities. This is particularly true for suppliers that engage in both original equipment (OE) service as well as independent after-market (IAM) businesses. This research aims to address these limitations for suppliers by developing a range of hazard rate models for core returns duration modeling. Models are also validated using data from a large global automotive supplier.