Abstract
The main purpose of this paper is to identify factors that affect sales volumes of sowing crops and develop a method for the most accurate forecasting of their sales to support decision making and improve the efficiency of business processes of agro-industrial companies. This article describes the developed approach to the forecasting of sales volumes of sowing crops, which includes the identification of factors that affect sales, the formation of a training sample, and a comparison of methods for constructing mathematical models. For the construction of forecasts, linear regression methods, random forests and a neural network are used. Also, the article describes a software platform that builds forecasts of sales of crops, using R and ShinyApps.