[Objective] To analyze the importance of the factors that influence the change of cultivated land area in order to predict the amount of cultivated land area resources, and to service the protection of cultivated land.[Methods] Taking Qingyang City of Gansu Province as a case study, the random forest algorithm was used to construct the prediction model of cultivated land area. The results were compared with those of BP neural network model, and the importance of the factors that influencing cultivated land area change was sorted.[Results] The relative error and root mean square error of the prediction results of the random forest algorithm were smaller than that of BP neural network, and the prediction accuracy was high and the results were stable. The cultivated land area in 2020, 2025 and 2030 was predicted to be 4.515×10⁵, 4.513×10⁵ and 4.512×10⁵ hm², respectively, showing a decreasing trend. The importance of the main influencing factors was ranked as:agricultural machinery general dynamics > agricultural population > GDP > fixed asset investment.[Conclusion] The random forest algorithm is suitable for the prediction of cultivated land area and can measure the importance of factors that influence the change of cultivated land area.