Monthly data on price indices of consumer goods and services as well as groups of some goods and the principal monetary indices in Lithuania are considered in this paper using methods of mathematical statistics. The main goal of this work is to construct mathematical models of the consumer price (ePI) index, fit for short-term prediction. Statistical dependency between prices and monetary indicators is investigated in the paper. Trends and seasonal components are estimated. Random fluctuations are described using autoregression models. Regressive models of prices and monetary indicators as regressors are constructed. Errors of indicator prediction using the proposed models are estimated. An expert analysis of the state of the national economy is made, taking into account changes in price, production, and unemployment indicators. Due to data inaccuracy and frequent recalculation of indicators, only a qualitative analysis was made without applying mathematical means.