Viewport prediction technologies are often used by most popular adaptive 360-degree video streaming solutions. These solutions stream only the content considered as being more likely to be watched by the final user, with the goal of reducing the volume of network traffic without compromising the user’s Quality of Experience (QoE). In this paper, we propose the Most Viewed Cluster algorithm (MVC), which is a hybrid viewport prediction method. It estimates the user viewport using two types of information: (i) the path of moving objects in the scene and (ii) the viewing behavior of previous users. Preliminary results show that MVC yields good results for long-term predictions.