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Currently, criminals profile (CP) is obtained from investigators or forensicpsychologists interpretation, linking crime scene characteristics and anoffenders behavior to his or her characteristics and psychological profile.This paper seeks an efficient and systematic discovery of nonobvious andvaluable patterns between variables from a large database of solved cases via aprobabilistic network (PN) modeling approach. The PN structure can be used toextract behavioral patterns and to gain insight into what factors influencethese behaviors. Thus, when a new case is being investigated and the profilevariables are unknown because the offender has yet to be identified, theobserved crime scene variables are used to infer the unknown variables based ontheir connections in the structure and the corresponding numerical(probabilistic) weights. The objective is to produce a more systematic andempirical approach to profiling, and to use the resulting PN model as adecision tool.

Modeling of Human Criminal Behavior using Probabilistic Networks