Person-borne weapons and explosives present a major threat to security in airports, government venues, and other highly populated or highly secure areas. With the rise of nonmetal threats, including improvised explosives, liquids, plastics, and ceramic weapons, metal detectors are no longer sufficient security measures. Pat-downs can identify these objects, but are viewed by the public as too physically invasive. Millimeter-wave imaging systems provide an alternative to both metal detectors and pat-downs by using electromagnetic radiation to detect any object underneath an individual’s clothing. The detection accuracy of these systems is limited by the current hardware configurations and software algorithms. Improvements to these systems can be investigated through modeling and simulation using various computational electromagnetic methods. Computational methods that are both fast and accurate are required in the design phase for improved millimeter-wave whole-body scanners. These methods are needed to model and understand the interactions of radiation with realistic human body types, weapons, and explosives and to efficiently explore complex hardware sensor designs. Fast and accurate methods are also required in the hardware implementation of millimeter-wave systems to enable real-time image reconstruction in high throughput security areas. Computational algorithms based on ray tracing, Physical Optics, and Finite Difference in the Frequency Domain methods are evaluated for feasibility for both simulation and implementation. Tradeoffs between the accuracy of field solutions and the time and memory required to solve for the solutions are considered in this work.