Measuring speech intelligibility for different hearing aid fitting methods in a simulated environment would allow rapid prototyping and early design assessment. A simulated performance intensity function (SPIF) test methodology has been developed to allow experimentation using an auditory nerve model to predict listeners' phoneme recognition. The test discriminates between normal hearing and progressively degrading levels of sensorineural hearing loss. Auditory nerve discharge patterns, presented as neurograms, can be subjectively ranked by visual inspection. Here, subjective inspection is substituted with an automated ranking using a new image similarity metric that can quantify neurogram degradation in a consistent manner. This work reproduces the test results of a real human listener with moderate hearing loss, in unaided and aided scenarios, using a simulation. The simulated results correlate within comparable error margins to the real listener test performance intensity functions.