A flow chamber image system was used to study the single cell growth of Pseudomonas Aeruginosa. A stochastic modeling process was applied to connect the growth of P. Aeruginosa single cells and cell colonies, and made it possible to simulate the population growth of P. Aeruginosa. Experimental bacteria growth viable counts using different initial inoculum sizes were detected to validate the simulation process. Meanwhile, many simulations were carried out to verify the effect of inoculum size on the lag time of P. Aeruginosa. The results indicate that the agreement between simulations and viable counts is good at both 25℃ and 35℃ and the simulation process can be one of methods for predicting the population growth of P. Aeruginosa. Through many simulations, it demonstrates that the lag time decreased from 12.52h to 6.33h at 25℃ and 8.61h to 4.01h at 35℃ as the initial inoculum size increased from 0CFU/mL to 100CFU/mL. The uncertainty and variability in bacteria cell growth are shown clearly in the simulation process. Also this method can be used as a reference to predict bacterial population growth and to study the lag behavior of microorganism.