Design of video encoders involves implementation of fast mode decision(FMD) algorithm to reduce computation complexity while maintaining the performance of the coding. Although H.264/scalable video coding(SVC) achieves high scalability and coding efficiency, it also has high complexity in implementing its exhaustive computation. In this paper, a novel algorithm is proposed to reduce the redundant candidate modes by making use of the correlation among layers. A desired mode list is created based on the probability to be the best mode for each block in base layer and a candidate mode selection in the enhancement layer by the correlations of modes among reference frame and current frame. Our algorithm is implemented in joint scalable video model(JSVM)9.19.15 reference software and the performance is evaluated based on the average encoding time, peak signal to noise ration(PSNR)and bit rate. The experimental results show 41.89% improvement in encoding time with minimal loss of 0.02 dB in PSNR and 0.05%increase in bit rate. Although H.264 / scalable video coding (SVC) achieves high scalability and coding efficiency, it also has high complexity in implementing its exhaustive computation. In this paper, a novel algorithm is proposed to reduce the redundant candidate modes by making use of the correlation among layers. A desired mode list is created based on the probability to be the best mode for each block in the base layer and a candidate mode selection in the enhancement layer by the correlations of modes among reference frames and current frame. Our algorithm is implemented in joint scalable video model (JSVM) 9.19.15 reference software and the performance is based on the average encoding time, The experimental results show 41.89% improvement in encoding time with minimal loss of 0.02 dB in P SNR and 0.05% increase in bit rate.