There are provided mechanisms for predicting a multimedia session MOS. The multimedia session comprises a video session and an audio session, wherein video quality is represented by a vector of per-time-unit scores of video quality and wherein audio quality is represented by is a vector of per-time-unit scores of audio quality. The multimedia session is represented by a vector of rebuffering start times of each rebuffering event, a vector of rebuffering durations of each rebuffering event, and an initial buffering duration being the time between an initiation of the multimedia session and a start time of the multimedia session. The method comprises generating audiovisual quality features from the vector of per-time-unit scores of video quality and the vector of per-time-unit scores of audio quality. The audiovisual quality features comprise: a vector of per-time-unit scores of audiovisual quality, calculated as a polynomial function of the vector of per-time-unit scores of video quality and the vector of per-time-unit scores of audio quality; a weighted combination of the per-time-unit scores of audiovisual quality, wherein the weights are exponential functions of a time since the start time of multimedia session and a multimedia session duration; a negative bias representing how a sudden drop in per-time-unit scores of audiovisual quality affects the multimedia session MOS; and a term representing a degradation due to oscillations in the per-time-unit-scores of audiovisual quality. The method comprises generating buffering features from the vector of rebuffering start times of each rebuffering event, calculated from the start time of multimedia session, and the vector of rebuffering durations of each rebuffering event. The method comprises estimating a multimedia session MOS from the generated audiovisual quality features and the generated buffering features.