System modeling is required to develop, analyze and predict the performance of solar facilities. Indirect solar dryers are typical systems as they are nonlinear and operate under floating weather conditions. In this paper, a Takagi-Sugeno fuzzy (TSF) model is used to predict the temperature inside the drying chamber for any season either in natural or forced convection. First, several experimental tests were performed on the studied dryer to establish its static and dynamic characteristics for different weather conditions. Second, measurements of the temperature inside the drying chamber were conducted around some operating points in both natural and forced convection. Around some chosen operating points, linear transfer functions was identified. The TSF system was used to combine all the identified linear models to develop a global one. Experimental tests were set up and used to evaluate the reliability of the developed model. The predicted behaviors are identical to the experimental ones with an RMSE (RMSE%) that remains under 0.4 degrees C (0.81%) in natural convection and 0.52 degrees C (1.94%) in forced convection. The developed TSF model leads to predict the thermal behavior in the dryer accurately and in very short time compared to other often used modeling techniques. (C) 2018 Elsevier Ltd. All rights reserved.