The agricultural sector, at the current stage of development, faces unique challenges dictated by the large-scale implementation of digital technologies in all fields of activity. Industry 4.0 in agriculture represents a new stage of development of this sector. Information products and technologies not only allow the creation and maintenance of databases, but also provide high speed of adaptation to change, building algorithms that can automate decision-making processes. Compared to traditional forms of management, the digitization of decision-making processes in agriculture contributes significantly to increasing the efficiency of production processes, storage, delivery of goods, provision of services, as well as to improving the efficiency of technologies and equipment applied in these processes. The research aims to examine the mathematical models that can be used to diagnose, monitor and predict the activity of agricultural enterprises at the current stage, as well as conceptualizing the need for new management models in the agricultural sector based on innovative digital technologies. The author supports the need to use mathematical and algorithmic models for processing and analyzing information obtained about farms based on database analysis, using multidimensional analysis and aggregate evaluation indicators, which provide a significant increase in the efficiency of management decisions. The mathematical methods presented allow to take into account not only the absolute values of the indicators of each analyzed enterprise, but also their rating in an analysis sample based on the economic and financial results achieved over several years of activity.