Membrane fouling occurs when the operating flux exceeds a certain point (i.e., critical flux). Critical flux has therefore been widely adopted to determine the initial operating flux in membrane bioreactor (MBR) processes. The flux steeping method currently used to measure the critical flux is time-consuming and uneconomical. This study was conducted to develop a novel approach for the evaluation of critical flux. Given that particle fouling is dominant during the initial fouling stage, we hypothesized that particle properties may be closely related to critical flux. A critical flux prediction model with an R2 of 0.9 was therefore derived, which indicates that particle properties regulate critical flux. The results imply that most of the fouling potential during the early stages of operation is caused by SS, and that the formation of cakes that comprise large particles is the dominant fouling mechanism. The new method proposed in this study reduced the measurement cost and time to evaluate critical flux by 3.5-and 8 times, respectively, compared to the flux-stepping method. In terms of practical application, the applicability of the model equation was identified by system reliability analysis, which indicates that the system failure increases significantly as the standard deviation of the variables increases. This study demonstrated that the prediction of critical flux and system reliability can be achieved through particle characteristic measurement. A similar approach is expected to be employed in real MBR plants as an economical and convenient fouling control strategy to solve problems involving resource shortages.