Abstract: Based on dynamic frame slotted ALOHA algorithm, a novel algorithm is presented to estimate the number of tags. Utilizing the slot information of the current frame and combining the Bayesian algorithm to get the probability distribution of the number of tags, the algorithm estimates the next frame's tags quantity more accurately. The simulation results show that the estimation errors of the number of tags remain stable around 1.4% and the channel throughput rate is close to the theoretical value 36.8% by using the algorithm, which proves the effectiveness of the algorithm.