Digital forensics examiners have a growing problem caused by their own success. The need for digital forensics is increasing and so are the devices that need examining. Not only are the number of devices growing, but so is the amount of information those devices can hold. One result of this problem is a growing backlog that could soon overwhelm digital forensics labs across the country. One way to combat this growing problem is to use digital triage to find the most pertinent information first. Unfortunately, although several digital forensics models have been created, very few digital triage models have been developed. This results in most organizations, if they perform digital triage at all, performing digital triage in an untested ad hoc fashion that varies from office to office. This dissertation will contribute to digital forensics science by creating and testing a digital triage model. This model will be semi-automated to allow for the use by untrained users; it will be as operating system independent as possible; and it will allow the user to customize it based on a specific crime class or classes. The use of this model will decrease the amount of time it takes a digital triage examiner to make a successful assessment concerning evidence. Advisors/Committee Members: David A Dampier (chair), Yoginder Dandass (committee member), Nan Niu (committee member), Christopher Bogen (committee member).