The smart farm is recognized as a solution for future farmers having positive effects on the sustainability of the poultry industry. Intelligent microclimatecontrol can be a key technology for broiler production which is extremely vulnerable to abnormal indoor air temperatures. Furthermore, better controlof indoor microclimate can be achieved by accurate prediction of indoor air temperature. This study developed predictive models for internal airtemperature in a mechanically-ventilated broiler house based on the data measured during three rearing periods, which were different in seasonal climateand ventilation operation. Three machine learning models and a mechanistic model based on thermal energy balance were used for the prediction. Theresults indicated that the all models gave good predictions for 1-minute future air temperature showing the coefficient of determination greater than 0.99and the root-mean-square-error smaller than 0.306℃. However, for 1-hour future air temperature, only the mechanistic model showed good accuracywith the coefficient of determination of 0.934 and the root-mean-square-error of 0.841℃. Since the mechanistic model was based on the mathematicaldescriptions of the heat transfer processes that occurred in the broiler house, it showed better prediction p...