We propose a proactive operational model for home appliances. Users of home appliances often have difficulty in operating appliances due to their high functionality, complex interface, which have many buttons, and users.' lack of knowledge. The current operational model of home appliances is a reactive model, which it is necessary for users to notify appliances of operational information. This causes an increased burden on the user to understanding correct operational information. To cope with these issues we propose a proactive operational model. In this model, appliances acquire the operational information by themselves, and provide users with their services based on that information. Based on this model, we have developed a middleware, called Proactive Support System for Networked Appliances (PRONA). PRONA is realized by acquiring information necessary for appliance operation and learning the users' operational pattern. PRONA consists of three modules, which are the information acquisition module, the suggestion composition module, and the information manager module. We evaluated the use of PRONA in a proactive television application. PRONA's quantitative evaluation criteria are its processing time, the accuracy of its suggestions for user' action, and its learning time for the user' operational pattern while varying the number of proactive components.