Turkey has 19.3 billion tons of lignite reserves and the vast majority of these Neogene lignite deposits are preferred for use in thermal power plants due to their low calorific value. The calorific value of lignite used in thermal power plants for electricity generation must be kept under constant control. In the control of calorific value, the estimation of the lower and higher heating values (LHV and HHV) of lignite is of great importance. In the literature, there are many studies that establish a relationship between the heating values of coal and proximate and ultimate analysis variables. In the studies dealing with proximate analysis data, it is observed that although the coefficients of the obtained multiple linear regression models (MRM) are statistically insignificant, these models are used to predict heating values because of the meaningful correlation coefficient. In this study, it is investigated whether moderator variables are effective on LHV estimation with proximate analysis data collected from forty-one lignite basins in different regions of Turkey, and a moderator variable analysis (MVA) model is developed to be used for the prediction of LHV. As a result of the study, it is found that the proposed MVA model is in accordance with observation values (coefficient of determination R ² = 0.951), and absolute and standard errors are also small. Therefore, it is concluded that the use of MVA to estimate the LHV of Turkey’s lignite is found to be more statistically meaningful.