Statistical multiplexing (SM) is a useful technique for transmitting multiple video streams over a channel while satisfying multiple simultaneous bandwidth and quality related constraints. Design of efficient SM algorithms is based on Rate and Distortion (R-D) information extracted from successive encoded frames. Good R-D models usually take into account inter-frame dependencies specified in terms of impact of encoding parameters of a given frame over the next one. A highly accurate low complexity rate and distortion model is proposed in this paper. A minimum number of R-D measurement points per stream is shown to be sufficient to predict the effect of interframe dependencies. Design of efficient SM algorithms satisfying the above mentioned performance constraints on the basis of the proposed R-D model is described.