A voice quality evaluation method, apparatus, and system comprises an obtained voice data packet is parsed, and a frame content characteristic of the data packet is determined according to a parse result, for example, the frame content characteristic is a silence frame and a voice frame. Then, a voice sequence is divided into statements according to the determined frame content characteristic, and the statements are divided into multiple frame loss events; after non-voice parameters are extracted according to the frame loss events, voice quality of each statement is evaluated according to a preset voice quality evaluation model and according to the non-voice parameters. Finally, voice quality of the entire voice sequence is evaluated according to the voice quality of each statement. By using this solution, prediction precision can be improved significantly, and accuracy of an evaluation result can be improved.