Haptic bilateral teleoperation holds promise for applications such as telemaintenance, remote manipulation, and disaster response, yet delivering precise, low-latency force and video feedback remains challenging. This study advances haptic bilateral teleoperation by combining live video with Model Mediated Teleoperation (MMT) to enable predictive force feedback. While this method has benefits, several non-trivial challenges, such as synchronizing the model with user's and remote robot's actions, arise. A novel algorithm is developed that allows the robotic device to replicate interactions predictively experienced by the operator. We validated this approach in a fully functional system that performs reliably despite significant network delays. The latency performance of the system is extensively characterized, achieving a motion-to-pixel latency of 58 ms. A user study revealed that operators did not perceive network latency of at least 75 ms, resulting in a 133 ms motion-to-pixel delay requirement. Additionally, a 5G latency analysis demonstrated that effective haptic teleoperation is achievable with both operator and remote ends connected via 5G. This provides a path away from strict latency requirements toward practical teleoperation solutions using currently available technology.