In automation flexible manufacturing systems, tool wear detection during the cutting process is one of the most important considerations. This study presents an intelligent system for online tool condition monitoring in drilling process. In this paper, analytical and empirical models have been used to predict the thrust and cutting forces on the lip and chisel edges of a new drill. Also an empirical model is used to estimate tool wear rate and force values on the edges of the worn drill. By using the block diagram of machine tool drives, the changes in the feed and spindle motor currents are simulated, as wear rate increases. To predict tool wear rate, fuzzy logic capabilities have been used to develop an intelligent system. The simulation results presented with MATLAB software show the effectiveness of proposed system for on-line drill wear monitoring. This is confirmed by comparing the measured and estimated values with each other in which the value of R-2 was obtained 0.9367 in the regression graph.