Data-mining helps to extract hidden predictive information from large databases. There are several tech-techniques and algorithms used for extracting the hidden patterns from the large data sets and finding the relationships between them Privacy preservation is an important factor in data mining. The problem of privacy preservation in data mining has become more important in recent years because of increasing need to store vast data about users. In this paper, a new privacy preserving approach is applied to decision tree learning. This approach converts the original sample datasets into a group of unreal datasets.