In terms of the problem “surplus fuel will increase fuel consumption” in Civil aviation transportation, together with the practical significance of flight time and fuel consumption per hour, this paper proposed a calculation method for the fuel capacity upon flight time. We analyzed the cases which include the collected flight time and fuel consumption of passenger airplane B737-800 on 2 000 kilometers routes, explored the numerical features of flight time by applying the chaotic time series theory, selected the neighborhood points by hamming distance and similarity, then proposed an improved adding-weight zero-rank local region prediction model especially for small datasets. Simulation results show that our proposed method could provide a better fit in multi-steps prediction than state-of-art adding-weight zero-rank prediction algorithms. The airline flight case of B737-800 and the predicted flight time were collected, and the proposed method has been validated. Numerical experiments show that this new method could save fuel capacity from 790 kg to 2 795 kg and reduce the fuel consumption from 0.6% to 1.47% during the same voyage.