The main purpose of the present study is to provide a proper model for forecasting energy demand of industrial sectors in Iran that can be used as a tool of scenario analysis to predict the emerging energy demand in future. In this way, this paper proposes a systematically developed model based on a previously performed exogeneity investigation of various quantified variables. A certain model among a collection of 43200 models with different inputs is chosen as the most appropriate model. Structure of all competing models is established according to logical conjunctive and disjunctive relationships between variables. Different combinations of the exogenous variables generate these models. An automated fuzzy decision-making (FDM) process determines the winner model, which is a log-linear model, among the other remaining models. Furthermore, the energy demand of industrial sector in Iran for the period of 2012 to 2020 is estimated.