The recovery of a DNA profile from the perpetrator or victim in criminal investigations can provide valuable ‘source level’ information for investigators. However, a DNA profile does not reveal the circumstances by which biological material was transferred. Some contextual information can be obtained by a determination of the tissue or fluid source of origin of the biological material as it is potentially indicative of some behavioral activity on behalf of the individual that resulted in its transfer from the body. Here, we sought to improve upon established RNA based methods for body fluid identification by developing a targeted multiplexed next generation mRNA sequencing assay comprising a panel of approximately equal sized gene amplicons. The multiplexed biomarker panel includes several highly specific gene targets with the necessary specificity to definitively identify most forensically relevant biological fluids and tissues (blood, semen, saliva, vaginal secretions, menstrual blood and skin). In developing the biomarker panel we evaluated 66 gene targets, with a progressive iteration of testing target combinations that exhibited optimal sensitivity and specificity using a training set of forensically relevant body fluid samples. The current assay comprises 33 targets: 6 blood, 6 semen, 6 saliva, 4 vaginal secretions, 5 menstrual blood and 6 skin markers. We demonstrate the sensitivity and specificity of the assay and the ability to identify body fluids in single source and admixed stains. A 16 sample blind test was carried out by one lab with samples provided by the other participating lab. The blinded lab correctly identified the body fluids present in 15 of the samples with the major component identified in the 16th. Various classification methods are being investigated to permit inference of the body fluid/tissue in dried physiological stains. These include the percentage of reads in a sample that are due to each of the 6 tissues/body fluids tested and inter-sample differential gene expression revealed by agglomerative hierarchical clustering.