Hyperspectral imaging combined with multivariate statistics is an approach to microanalysis that makes the maximum use of the large amount of data potentially collected in forensics analysis. This study examines the efficacy of using hyperspectral imaging-enabled microscopies to identify chemical signatures in simulated bioagent materials. This approach allowed for the ready discrimination between all samples in the test. In particular, the hyperspectral imaging approach allowed for the identification of particles with trace elements that would have been missed with a more traditional approach to forensic microanalysis. The importance of combining signals from multiple length scales and analytical sensitivities is discussed.