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controlling and producing them. Events from a few years ago caused by Listeria monocytogenes detected on cantaloupes, which caused 32 deaths and 1 miscarriage [16] and the recent case of suspected contamination by the same bacteria of sliced apples and withdrawal of entire batches of the product in November 2013 [4] showed how important it is for food producers to have access to precise information about the growth time and growth rate of microorganisms in stored products.Listeria monocytogenes is one of 19 species of the genus Listeria and the second, next to Listeria ivanovii, showing pathogenic properties [15]. It is a Gram-positive bacillus, which lives intracellularly and is the etiological factor of listeriosis. Bacteria belonging to this species have the highest virulence of all foodborne pathogens (20-30 % of infections are fatal), where the most pathogenic properties were noted for serotype 4b [18]. An example of this can be the USA-approximately 2500 cases and 500 deaths per year [5], thereby causing a higher mortality rate than Salmonella sp. or Clostridium botulinum. The main symptoms of listeriosis are septicemia, meningitis, encephalitis, corneal ulcer, pneumonia, and infections of the uterus in pregnant women, which can lead to a miscarriage or intrauterine fetal death [6,9,10, 13,22].Determining the bacterial growth, including Listeria monocytogenes, on different matrices, both fresh and processed, is the role of predictive microbiology. Within it, so-called growth models are formed allowing to determine the growth rate of microorganisms depending on the environmental conditions [20]. The information from modeling is used in the creation of databases, such as the ComBase Predictor (combined database for predictive microbiology), allowing to generate a model based on set variables that have an influence on bacterial growth, such as the pH, a w , temperature, concentration of NaCl [8,14]. AbstractThe quality and microbiological safety of produced and stored food is a challenge for its producers and official control. Numerous examples have shown how important it is for them to have access to precise data about the growth time and rate of microorganisms in stored products, especially in the case of those which are the etiology of digestive system diseases such as Listeria monocytogenes. It is one of the most virulent foodborne pathogens, showing a mortality rate of approximately 20-30 %, which is the highest among food microbiota. In order to determine the microbial growth kinetics in time on food matrices, socalled growth modeling is used. It allows to determine the growth of microorganisms in time and depending on the temperature, pH, water activity (a w ), or content of acids. In this paper, we verified the growth model of Listeria monocytogenes on cucumber and zucchini with an existing model in the ComBase Predictor.