Understanding the purpose of why sensitive data is used could help improve privacy as well as enable new kinds of access control. In this paper, we introduce a new technique for inferring the purpose of sensitive data usage in the context of Android smartphone apps. We extract multiple kinds of features from decompiled code, focusing on app-specific features and text-based features. These features are then used to train a machine learning classifier. We have evaluated our approach in the context of two sensitive permissions, namely ACCESS_FINE_LOCATION and READ_CONTACT_LIST, and achieved an accuracy of about 85% and 94% respectively in inferring purposes. We have also found that text-based features alone are highly effective in inferring purposes.