Location-related mobile device evidence is increasingly used to address forensic questions in criminal investigations. Evaluating this form of evidence, and expressing evaluative conclusions in this forensic discipline, are challenging because of the broad range of technological subtleties that can interact with circumstantial features of cases in complex ways. These challenges make this type of digital evidence prone to misinterpretations by both forensic practitioners and legal decision-makers. To mitigate the risk of misleading digital forensic findings, it is crucial to follow a structured approach to evaluation of location-related mobile device evidence. This work presents an evaluation framework widely used in forensic science that employs scientific reasoning within a logical Bayesian framework to clearly distinguish between, on the one hand, what has been observed (i.e., what data are available) and, on the other hand, how those data shed light on uncertain target propositions. This paper provides case examples to illustrate the advantages and difficulties of applying this approach to location-based mobile device evidence. This work helps digital forensic practitioners follow the principles of balanced evaluation and convey location-related mobile device evidence in a way that allows decision-makers to properly understand the relative strength of, and limitations in, digital forensic results.