Sounds like a good exercise. Crime scenes generate a lot of messy data—fingerprints, DNA, timestamps, locations. To turn that into a model you need to clean the data, define variables, and apply statistical techniques. My usual approach starts with clear objectives, defines the key metrics, then builds a regression or classification model with cross‑validation. If you want to compare, let’s look at the variables you’re using, the data quality, and how you validate the predictions. That will give us a baseline for how the crime‑scene workflow stacks up against standard business analytics.