The shopping mall domain is a dynamic and unpredictable environment. Traditional techniques such as fundamental and technical analysis can provide investors with some tools for managing their shops and predicting their business growth. However, these techniques cannot discover all the possible relations between business growth and thus, there is a need for a different approach that will provide a deeper kind of analysis. Data mining can be used extensively in the shopping malls and help to increase business growth. Therefore, there is a need to find a perfect solution or an algorithm to work with this kind of environment. So we are going to study few methods of pruning with decision tree. Finally, we prove and make use of the Cost based pruning method to obtain an objective evaluation of the tendency to over prune or under prune observed in each method.