Lactic acid bacteria (LAB), especially Weissella viridescens and Leuconostoc mesenteroides species, actively contribute to the spoilage of meat products. The large amount of growth data provided by the combination of conventional and molecular methods, such as the quantitative Polymerase Chain Reaction (qPCR) method, has provided important information about the growth of each species during shelf-life tests. These allow microbial classification into different classes according to their behavior in a food matrix. Therefore, the purpose of this research was to develop a Molecular Predictive Model (MPM) using the SYBR® Green qPCR method for describing the growth of W. viridescens and L. mesenteroides strains in pure and mixed culture, under isothermal storage conditions (4, 8, 14 and 30 °C). The model calibrated by the qPCR method was compared to a Conventional Predictive Model (CPM) using the growth data obtained by the Plate Count (PC) method. The Baranyi and Roberts (BAR), modified Gompertz (GOM), and modified logistic (LMZ) models were fitted to the experimental growth data. The results showed that the models were adequate to describe the growth curves of W. viridescens at 4, 8, 14, and 30 °C in pure culture and mixed culture with L. mesenteroides at 8 °C. Adaptation and exponential phases were evident in all models. The statistical indexes values were better for the fitting of the BAR model to the molecular data. The Exponential secondary model represented well the temperature dependence on the µmax parameter for all MPM and CPM. These results highlight the importance of combining the SYBR® Green qPCR method with predictive modeling to provide a new tool for studying the evolution of LAB species under refrigerated conditions, allowing the establishment of parameters that can lead to an increase in the shelf-life of food spoiled by these bacteria.