The modeling of forecasting of the firm financial indicators performance by means of extrapolation method on the basis of polynomial function is carried out in the article. The authors empirically prove that the polynomial trend accurately reflects the dynamics of the firm's revenue with the seasonal nature of sales. For forecasting revenue, characterized by seasonal dynamics, the article developed an algorithm for constructing a model. For the purpose of approbation of the author's forecasting algorithm, the revenue forecast was modeled according to quarterly reports of Plant of Electrical Installation Products (PEIP) TatelectromontazhJSC for the period 2014 – 2016. Based on the obtained modeling results, the authors proved that modeling with the use of a polynomial trend provides a high-quality forecast of the dynamics of the firm's revenue in the conditions of a dynamically changing external environment. The proposed method for forecasting the revenue of PEIP TatelectromontazhJS Callows you taking into account the impact of changes in the macroeconomic environment. The results of logical modeling also confirm the reliability of the results of the constructed forecast model. Practical implementation of the proposed modeling methodology revealed the following features. First, to compile a forecast, it is necessary to accurately identify the duration of the season; Secondly, if there is enough data, the method gives a good approximation and can be effectively used in forecasting the sales volume with the seasonal component.