Data mining helps end users extract valuable information from large databases. In medical field, practioners have with them mountains of patient data. Any successful medical treatment is based after complete analysis of vast amount of patient data. But practitioners are often faced with the problem of extracting relevant information and finding certain trend or pattern that may further help them in the analysis of treatment of any disease. Data mining is such a tool, which sifts through voluminous data and presents the data of essential nature. In this paper we have focused on managing asthma in children. The approach used is C4. 5 algorithm. Our predictive model will help in categorizing of asthma and also suggesting the best possible treatment. The choice of treatment is dependent on severity of the disease. The trick in building a successful predictive model is to have some data in the database that describes what has happened in the past. Classification method is designed to learn from the past successes and failures and then predict the outcome. Decision trees are a from of data mining technology that has been around for almost 20 years. They are increasingly used for prediction.