In this paper we apply data mining analysis to study Internet path performance. We show how a data mining system can be used by end-users in this application. Trace-route packet probing technique is used for Internet measurements. The data set is mined using neural clustering and tree classification mining functions available in IBM Intelligent Miner. We discover from the measured data sets how the round-trip times of the packets and the number of hops they pass vary with the day of the week and the time of the measurement. The decision tree model shows good accuracy of 97% and may be useful to predict Internet path performance.