Partial spoilage data are generated by simulating experimental methods frequently used in food science. The basic experimental model that is simulated is as follows: N tubes (or cans) of substrate (food) are inoculated with a microbiological contaminant (e.g. PA 3679 or C BotuZinum). These replicates are then subjected to a lethal environment (heat or radiation, etc.) and after incubation the replicates are tested to determine the number of replicates with viable contaminants remaining. Exact counts are not possible. The algorithm developed has many useful options, so that the simulation can be used within many areas of food science. The basis of the methodology is probabilistic, and food scientists may use it to generate replicate data necessary for statistical analyses. The technique can be useful for understanding the underlying microbiological phenomena. Repetitive runs may be used for comparative analysis with actual experimental results, in an inexpensive way. The methodology also provides a possible explanation of 'skips' and 'tailing' as has been observed in partial spoilage data.