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. we present an end-to-end approach for PFP inference and its associated tool, POPI. This is the 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. 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.