Selecting an optimal web service among a list of functionally equip agent web services still remains challenging issue. For Internet services, the presence of low- performance servers, high latency or overall poor service qualities can’t ran s late into lost sales, user frustration, and customers lost. Ith is paper, we propose a novel method d for QoS me trifurcation based on Hidden Markov Models ( HMM ) , which further suggests a n optimal path f or the execute on of user requests . The technique we show can be use d to measure and predict he be have or of Web Services in term s of response time , and can’t hubs used to rank services quantitatively rather than just qualitatively. We demonstrate the feasibility and usefulness of our methodology by drawing permits on re al world da t a. The results have shown how our proposed method can help the user to automatically elect the most reliable Web Service taking into account several metrics, among them , system predictability and responses me variability. Later ROC curve shows a 12 percent improvement in prediction accuracy using HMM