Abstract
This article is devoted to the consideration of how information technologies are used in practice in the agro-industrial complex at the present time. The main purpose of the study is to substantiate the effectiveness of these methods and to identify the main areas of use. The paper discusses the use of machine learning models to work with data in agriculture. The relevance of the study is justified by the fact that industry, as well as agriculture, are one of the most priority areas in our country. There is a need for the use of adaptive devices and new methods that will make it possible to achieve significant success in this area. The article is devoted to the consideration of the code implemented in Python, which can predict crop yields with high accuracy. By applying adaptive learning models and comparing different statistical models with each other, it is possible to identify the most accurate predictive indicators.