Multi-scale　structural　similarity　(MS-SSIM)　is　a　commonly　used　full-reference　quality　assessment　metric.　Since　the　original　video　is　required　for　reference,　it　is　not　suitable　to　be　applied　in　real-time　assessment　of　network　video　quality.　In　this　paper,　a　no-reference　MS-SSIM　video　quality　assessment　model　based　on　H.264　bitstream　was　proposed.　First,　I-frame　and　P-frame　encoding　mode　and　motion　vector　parameters　from　H.264　bitstream　were　extracted　from　H.264　bitstream,　which　then　were　statistically　analyzed　to　characterize　the　richness　of　the　texture　and　the　intensity　and　complexity　of　the　motion　of　the　video.　Second,　the　parameters　were　combined　with　quantization　parameter　to　form　the　bitstream　feature　parameter　set,　and　support　vector　regression　(SVR)　was　finally　applied　to　the　relationship　between　the　bitstream　feature　parameters　and　MS-SSIM　to　predict　the　video　quality　metric　of　MS-SSIM　for　H.264　bitstream.　The　proposed　model　only　uses　the　parameters　extracted　from　the　video　bitstream　and　does　not　demand　to　decode　the　video　bitstream　completely.　Compared　with　a　state-of-the-art　no-reference　bitstream　prediction　model,　the　proposed　model　can　achieve　higher　prediction　accuracy.　©　2018,　Editorial　Department　of　Journal　of　Beijing　University　of　Technology.　All　right　reserved.