Data mining is one of the widespread research areas of present time as it has got wide variety of application to help people of today’s world. It is all about finding interesting hidden patterns in a huge history database. In this research work, data mining is comprehensively applicable to a domain called placement chance prediction, since taking wise career decision is so crucial for all of us for sure. A strategy to predict the overall absorption rate for every branches as well as the time it takes for all the students of a particular branch to get placed etc. are also proposed. From each combination of attributes from the history database of student records, corresponding placement chances is computed and stored in the history data base. From this data, various popular data mining models are built and tested. These model can be used to predict the most suitable branch for a particular new student with one of the above combination of criteria. A strategy to predict the overall absorption rate for various branches as well as the time it takes for all the students of a particular branch to get placed etc. are also proposed. The proposed method is tested on the data set provided by A.I.M.T college Lucknow and data is passes through the various data mining model, namely decision tree ,neural network and navie bayes classifier on area of the application to a domain, development of classifier and future outcomes were also configured on this thesis. At last this research work puts forward the data mining algorithm namely C 4.5 * stat for numeric data sets which has been proved to have competent accuracy over standard benchmarking data sets called UCI datasets. It also proposes to improve the standard C 4.5 algorithm.