The objective of the paper was to construct mathematical bacteria growth models of the Pseudomonas spp. bacteria occurring in model meat products considering the two following factors: time and temperature. For the purpose of the investigations performed, there was used a ‘model’ of the meat product representing a group of meat products made of minced meat. The investigation results obtained made it possible to construct first-order Gompertz and logistic models which appropriately described the growth of bacteria in minced meat products during their storage at various temperatures. The constructed Conline linear models were not sufficiently matching. The second-degree Ratkowsky model appeared to be the most suitable for the purpose of assessing the growth rate of the groups of microorganisms. The second-degree poly-nominals appeared to be the most suitable to describe, in the form of response surfaces, the effect of two variables on the growth of selected groups of microorganisms in meat products. Additionally, an attempt was made to apply this new tool, i.e. neural networks, to microbiological prognoses.