An important aspect of research in the continued development of cochlear implants is the in vivo assessment of signal processing algorithms. One technique that has been used is evoked potentials, the recording of neural responses to auditory stimulation. Depending on the latency of the observed response, the evoked potential indicates neural activity at the various neurological structures of the auditory system. Electrically evoked ABRs are commonly measured in hearing-impaired patients who have cochlear implants, via electrical stimulation delivered by electrodes in the implanted array. This research explores the use of MATLAB for the purpose of developing a model for electrically evoked auditory brainstem responses (ABRs). The simulation model developed in this study takes as its input the stimulus current intensity level, and uses function vectors and equations derived from measured ABRs, to generate an approximation of the evoked surface potentials. A function vector is used to represent the combined firing of the neurons of the auditory nervous system that are needed to elicit a measurable response. Equations have been derived to represent the latency and stimulus amplitude scaling functions. The simulation also accounts for other neural activity that can be present in and contaminate an ABR recording, and reduces it through time-locked averaging of the simulated response. In the MATLAB simulation, the model performs well and delivers results that compare favorably with the results measured from the research subjects.