In this paper, fuzzy modeling for the control of basic oxygen furnace (BOF) processes is proposed. BOF is a widely preferred and effective steel making method due to its higher productivity and considerably low production cost. Therefore, today almost 65% of the total crude steel production in the world is met by using the BOF method. Higher steel output at lower cost is one of the main objectives of modem steel making methods. In order to accomplish this objective, fuzzy modeling was employed in this study in order to control some variables related to the BOF process. Fuzzy modeling and control in BOF promise a solution to the strongly non-linear problems associated with the process, which have so far proven extremely difficult to be solved by conventional control methods. Data set was selected as inputs from the real empirical BOF data in an integrated steel plant based in Turkey. Although there were negligible deviations from the target values, most of the fuzzy results obtained using MATLAB-Fuzzy Logic Toolbox version 5.0 were found to be acceptable. As a result of the application of the proposed modeling, acceptable levels of compatibility were achieved compared to the empirical BOF data and targeted steel composition. The paper indicates how fuzzy logic would be effectively used for improved process control of BOF furnace in steel making industry. (C) 2004 Elsevier B.V. All rights reserved.