Аннотация:In this paper, we study an algorithm for obtaining the most efficient model for predicting the amplitude of the geomagnetic Dst index, based on lowering the input data dimension by gradually discarding input features. This task is relevant, since the selection of significant input data is necessary for the effective use of machine learning methods. The study was carried out on the basis of the following machine learning methods: artificial neural network of the multilayer perceptron type, gradient boosting, linear regression. Comparison of the effectiveness of the listed methods is carried out.