The emergence of DNA analysis as an effective forensic tool in the 1990s was a revelation, in that for the first time it was possible to quantify the degree of association between a crime scene sample and a suspect.  It also had the effect of shining a light on other forensic practices, most of which lack the rigorous and widely accepted scientific foundations of DNA profiling and for which error rates are largely unknown. In the US criminal justice system, jurors choose between two competing hypothesis:  the suspect is the source of the evidence found at the crime scene or is not.  We discuss a likelihood ratio framework for assessing the probative value of evidence, that relies on Bayes’ theorem and that – at least in principle – can be adapted to any time of evidence.  We present two examples to illustrate its application, one using the chemical composition of glass fragments and the other one using information about the surface topography of bullet lands.