Dynamic Adaptive Streaming over HTTP(DASH) is a video transmission ptotocol to adapt to different network conditions and heterogeneous client devices. The client first requests and parses the Media Presentation Description(MPD) file from the DASH server to obtain basic information including the average bitrate list and segment URLs. After that, the adaptive bitrate(ABR) algorithm decides the quality of the next requested segment based on the network and buffer conditions. However, there is a big discrepancy between the segment size calculated with this coarse-grained average bitrate and the real size due to the constantly changing video scenes, which is especially obvious for variable bitrate(VBR) encoded videos. And this error is transparent to the ABR algorithm. This paper first analyzes and confirms the inter-layer correlation of scalable video coding(SVC) encoded contents, then designs a segment size prediction module to cooperate with the ABR algorithm. Experimental results show that predicting a certain enhancement layer(EL) segment size by all its previous layers can increase the probability that the predicted value falls within the accurate interval by 20% −58% compared to predicting the EL only by base layer(BL). Besides, the ABR algorithm assisted with size prediction module can increase the average bitrate by 29.2%, reduce the average bitrate switches by 13.4% and the average rebuffering events by 78.7% compared with the independent ABR algorithm.