Short tandem repeat (STR) profiling from DNA samples has long been the bedrock ofhuman identification. The laboratory process is composed of multiple procedures thatinclude quantification, sample dilution, PCR, electrophoresis, and fragment analysis. Theend product is a short tandem repeat electropherogram comprised of signal from allele,artifacts, and instrument noise. In order to optimize or alter laboratory protocols, a largenumber of validation samples must be created at significant expense. As a tool to supportthat process and to enable the exploration of complex scenarios without costly samplecreation, a mechanistic stochastic model that incorporates each of the aforementionedprocessing features is described herein. The model allows rapid in silico simulation ofelectropherograms from multicontributor samples and enables detailed investigations ofinvolved scenarios. An implementation of the model that is parameterized by extensivelaboratory data is publically available. To illustrate its utility, the model was employed inorder to evaluate the effects of sample dilutions, injection time, and cycle number on peakheight, and the nature of stutter ratios at low template. We verify the model’s findings bycomparison with experimentally generated data.