The forecast dramatic growth, of the number of Machine-to-Machine (M2M) communications, challenges the traditional networks of Mobile Network Operators (MNO). In fact, a large number of devices may attempt simultaneously to access the base station, which may result in severe congestions at the random-access channel (RACH) level. To alleviate such congestion while regulating the M2M devices' opportunities to transmit, the Access Class Barring (ACB) process was proposed. In this article, we proposed a novel implementation of the ACB mechanism in the context of multiple M2M traffic classes. Based on a scheduling algorithm, we have applied a PID controller to adjust dynamically multiple ACB factors related to each class category, guaranteeing a number of devices around an optimal value that maximizes the Random Access (RA) success probability. The obtained results demonstrate the efficiency of the proposed mechanism by increasing the success probability and minimizing radio resources' underutilization with respect to each class priority.