Abstarct: One way to select a drill bit is to use a dull bit grading table. This dull bit grading table is a routine method for noting and recording failures and effects of controllable and uncontrollable drilling parameters on the drill bit. The drill bit coming out of the well contains very significant information about the drilling conditions in which we can extract maximum information from it. Due to the practical drilling conditions and the uncertainty in the bit selection, in this research for the first time, we attempted to assess the data of the used drill bit by the Monte Carlo simulation method. For this purpose, first, the data were preprocessed and prepared for using in the Monte Carlo simulation. Then the performance index relationship was defined as a new model for determining the degree of dull. Then, according to the previous data, an algorithm was used to generate artificial data using Monte Carlo and Monte Carlo bootstrap methods. In the Monte Carlo method, among the four drills studied (517, M423, M223 and M1665), the M223 drill with a performance index of 0.73 was selected for a 12-1/4” hole size with 99% accuracy. In the Monte Carlo bootstrap method, the probability of passing the performance index was used to select the drill. The results showed that with increasing the performance index, the exceedance probability has decreased sharply so that for the performance index greater than 0.65, the Exceedance probability falls below 5%, which indicates the impossibility of drills achieving this level of performance. However, among the four drills studied, the M223 drill showed a higher probability of drilling and is therefore a more suitable drill for drilling.