The objective of this paper was to construct and develop predictive models, the application of which it makes possible to assess the shelf-life of meat products produced of ground beet meat. There were constructed primary linear models with a free parameter of growth of the total viable count (TVC) [log cfu/g] containing all the analyzed variables (the addition of NaCl and NaNO₂, storage time, and temperature); the said models were constructed using a linear regression, as well as Gompertz (G) and logistic (L) response surface models of the growth of total viable count (TVC) [log cfu/g] including the impact as exerted by NaCl and NaNO₂ added. The computation was performed using a nonlinear least squares method supported by the Gauss-Newton  algorithm. On the basis of the results obtained from the microbiological analyses performed, linear models of the total viable count (TVC) were developed; with those models, it was possible to assess the shelf-life of meat products, and, first of all, of those stored at a low temperature (5ºC). The Gompertz and logistic surface response models obtained and statistically well fitted, enable manufacturers to satisfactorily predict the shelf-life of meat products, in particular of those stored at a higher storage temperature (15ºC).