Packet classification enables network routers to provide advanced network services including network security, quality of service (QoS) routing, and multimedia communications. In order to classify a packet, network nodes must perform a search over a set of filters using multiple fields of the packet as the search key. Viewing the classification problem geometrically, classifying an arriving packet is equivalent to finding the highest priority hyperrectangle among all hyperrectangles that contain the point representing the packet. The R-tree and its variants, being among the most popular access methods for points and rectangles, have not been experimentally evaluated and benchmarked for their eligibility for the packet classification problem. In this paper we investigate how the R*-tree, a dynamic index structure for spatial data, is suited for packet classification. To this end we will benchmark R* with two representative classification algorithms using the ClassBench tools suite.