Social instant messaging services (SMS) such as WhatsApp, Snapchat and WeChat, have significantly changed the way people work, live, and communicate, attracting increasing attention from multiple disciplinary including computer science, sociology, psychology, and physics. In SMS, social groups play a very important role in supporting communication among multiple users. An interesting question arises: what are the dynamic mechanisms underlying the group evolution? Or more specifically, in an existing group, who should be invited to join? In this paper, we formalize a novel problem of predicting potential invitees of groups. Employing WeChat, the largest social messaging service in China, as the source for our experimental data, we develop a probabilistic graph model to capture the fundamental factors that determine the probability of a user to be invited to a specific social group. Our results show that the proposed model indeed lead to statistically significant prediction improvements over several state-of-the-art baseline methods.