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Packet forwarding prioritization (PFP) in routers is one of the mechanisms commonly available to network operators. PFP can have a significant impact on the accuracy of network measurements, the performance of applications and the effectiveness of network troubleshooting procedures. Despite its potential impacts, no information on PFP settings is readily available to end users. In this paper, we present an end-to-end approach for PFP inference and its associated tool, POPI. This is the first attempt to infer router packet forwarding priority through end-to-end measurement. POPI enables users to discover such network policies through measurements of packet losses of different packet types. We evaluated our approach via statistical analysis, simulation and wide-area experimentation in PlanetLab. We employed POPI to analyze 156 paths among 162 PlanetLab sites. POPI flagged 15 paths with multiple priorities, 13 of which were further validated through hop-by-hop loss rates measurements. In addition, we surveyed all related network operators and received responses for about half of them all confirming our inferences. Besides, we compared POPI with the inference mechanisms through other metrics such as packet reordering [called out-of-order (OOO)]. OOO is unable to find many priority paths such as those implemented via traffic policing. On the other hand, interestingly, we found it can detect existence of the mechanisms which induce delay differences among packet types such as slow processing path in the router and port-based load sharing.