The development of technology over the past few decades have been quite prominent and this has led to the invention of many beneficial and powerful Innovations. These innovations not only left an impact to the society’s way of living, but it also led to one of the most significant invention, which is smartphone. From just merely a device used for making or receiving calls, smartphone have evolved to a device that could help aid us in completing daily tasks and transactions. Such practicality has made it into a form of necessity in our life. With smartphone, most of the data generated contains sensitive and confidential data which could be exploited by hackers. Besides exploitable data, other factors such as granting excessive permission to applications, drive-by malware download, and data leakage can also be considered as mediums for hackers to exploit personal information. Thus, protecting the privacy of this data is of the essence. In light with such need, this research will use an existing data collector to download the data. The data collected will be analyze using classification technique in Machine Learning. Further analysis will be conducted to identify the most accurate classification algorithm in predicting the risks of using smartphone. This study is able to predict risk among users to reduce the likelihood of being hacked.