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Understanding Forensic Intelligence: The NIJ Framework

NCJ Number
Date Published
November 2023
2 pages

This publication provides a quick reference guide to the National Institute of Justice’s (NIJ) framework for understanding forensic intelligence.


This publication describes and illustrates the National Institute of Justice’s (NIJ) framework for understanding forensic intelligence. “Forensic intelligence” describes using forensic data early in an investigation, when that information can accelerate the process of solving the case. It also means using data across cases to understand crime trends and identify links between cases. The forensic results might not be confirmed and ready for court yet, but they are a powerful tool for making connections between evidence, suspects, cases, and sites of crime. That information can guide law enforcement away from dead ends and toward meaningful leads. The key to forensic intelligence is making data actionable as quickly as possible, so results leave the laboratory fast enough to steer law enforcement’s actions. Forensic data can also reveal patterns to help officers disrupt ongoing crimes and prevent new ones, instead of responding only to crimes that have already happened. To implement a forensic intelligence system, law enforcement agencies do not have to completely change their current intelligence analysis or investigation processes. They need to reexamine how they collect information for their cases and how they communicate with their partners, specifically their forensic laboratory components. Adopting a forensic intelligence model does not mean discarding existing intelligence strategies. Instead, forensic intelligence approaches (represented as yellow arrows) can be built into existing investigation processes without changing the entire workflow of an individual case. Early use of forensic data and preliminary results in the investigation cycle can generate useful investigative leads and bring about faster case resolution. Processes that were linear or siloed are bridged by a holistic view of data, overcoming linkage blindness and allowing connections to be made that were not visible before.

Date Published: November 1, 2023