A novel future frame extrapolation algorithm using the future cost volume is proposed in this work. First, we develop the future cost volume to estimate motion vectors from a future frame to input frames. Second, we generate two future frame candidates by back-ward warping the input frames using the future motion vectors. Finally, we develop a synthesis network, which aggregates the two candidates to reconstruct the future frame faithfully. Experimental results demonstrate that the proposed algorithm significantly outperforms state-of-the-art extrapolators on various datasets.