Technical Abstract: The objective of this research is to optimize a new mathematical equation as a primary model to describe the growth of bacteria under constant temperature conditions. An optimization algorithm was used in combination with a numerical (Runge-Kutta) method to solve the differential form of the new growth model in search for an optimized the lag phase transition coefficient (LPTC) that defines the adaption and duration of lag phases of bacteria prior to exponential growth. Growth curves of Listeria monocytogenes, Escherichia coli O157:H7, and Clostridium perfringens were analyzed to obtain the optimized lag phase transition coefficient. An optimized LPTC was obtained by numerical analysis of bacterial growth curves. With a new LPTC, the new growth model could be used to accurately describe the bacterial growth curves with three distinctive phases (lag, exponential, and stationary). The new optimized LPTC significantly improved the performance and applicability of this model. It can be used as an alternative primary model for bacterial growth if the bacterial adaption is more significant in controlling the lag phase development.