[Abstract] In view of the bimodal distribution of short-voyage fuel consumption under the influence of multiple factors, this paper proposes a method combining Gaussian mixture clustering (GMM) and random forest (RF) to estimate the short-range fuel consumption. The algorithm first uses GMM to cluster short-range fuel consumption data to obtain clusters of two different shapes. After that, the two clusters are sampled at different sampling rates, the sample subset is constructed, and the regression tree is used for each subset. Finally, the CART decision tree is used in parallel to obtain random forest for short-range fuel consumption estimation. The comparison experiments were carried out on the same model and route, and different flight data. The results show the effectiveness of the proposed algorithm.