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The aim of this paper is the analysis of methodology for selecting the best model for forecasting of fuelwood demand in Greece for the years 2020, 2025 and 2030 with a final objective the decision-making in the sector of forest bioenergy. A complete time series of historical data exists that concerns: (a) the consumption of fuelwood and (b) the six most important from the independent variables that could influence the consumption of fuelwood, whose data cover the time period 1989-2010. The evaluation and choice of the best model was realized with the help of the following six statistical criteria: (a) the size of standard error of theoretical values of dependant variable, S. E.; (b) the value of adjusted R square (R 2 ); (c) the non-existence of autocorrelation among the residuals (ei) through the criterion Durbin-Watson; (d) the statistical significance of models coefficients through t criterion; (e) the statistical significance of models through F criterion and (f) the non-existence of multicolinearity through the values of Variance Inflation Factor.

Methodology for Selecting the Best Model for Forecasts: The Case Study of Forest Bioenergy