Abstarct: The purpose of any drilling operation is to drill in the shortest possible time to minimize the costs in compliance with the safe operations. The concept of time of any drilling operation can be stated in terms of bit’s rate of penetration (ROP). There are several parameters that impact the rate of penetration. A mathematical relationship between these parameters and ROP assists in increasing the drilling speed by selecting optimum parameters. Due to the frequency of fractured formations in the South Zagros Basin up to 3000 meter, air and foam drilling method is an adequate alternative to the formal mud drilling. This study aims to mathematically relate ROP to mechanical (weight on bit, rotary speed), hydraulic (air flow rate, liquid flow rate) and local (formation hardness, depth) parameters in foam drilling to achieve the maximum rate of penetration. A commercial hydraulic air drilling software was used to calculate the optimum air flow rate for decreasing the problem of Shanul field in air and foam drilling. The optimum air injection rate was estimated between 1000 to 2000 CFM. A rate of penetration model has been predicted by a designed artificial neural network (ANN) using real data of 2 wells, namely Shanul #6 and #10. The corroletion coefficient of training, validation and test process of ANN were calculated to be equal to 0.9995, 0.9992 and 0.9973 respectively. After checking of the ANN model’s accuracy, it was then used for predicting of the ROP in design of experiment (DOE) to make a simple correlation between effective parameters and ROP using MiniTab software. Finally the most important of drilling parameters on ROP for 26, 17.5 and 12.25 (inch) holes has been investigated and ROP has been optimized.