Nowadays, the volume of data grows with an increasingly rate. Daily growth of data, needs new techniques that intelligently analyses these data and discover the hidden knowledge of them. Data mining provides some tools for analyzing mass databases, discovering processes, patterns and knowledge. Having a massive database, Esfahan Mobarakeh steel company, is considered as a comprehensive case for applying data mining techniques. The galvanizing line of steel sheets, with the ability of producing 200000 tons of galvanized steel sheets per year, is an important production line in this company. The mechanical specifications of galvanized sheets are the most important parameters that must be controlled exactly because they affect the product quality considerably. For the first time, in this work, data mining techniques are applied for analyzing the database of Esfahan Mobarakeh steel company and finally some models are presented for forecasting of mechanical specifications of galvanized sheet. These models forecast the mechanical specifications of the galvanized sheets and also show the effect of furnace heat and velocity of production line on the mechanical specifications. Finally these forecasted specifications will be compared with the existing standards and some results are represented.