Application of Bayes’ theorem in assessing recidivism risk in a serial rapist: a case study
Application of Bayes’ theorem in assessing recidivism risk in a serial rapist: a case study

Summary/Abstract: The assessment of recidivism risk among sexual offenders represents one of the most challenging issues in criminological and forensic practice, particularly in cases involving multiple repeatoffenders, where available data are often fragmentary and the degree of uncertainty is high. Theaim of this paper is to demonstrate the application of Bayes’ theorem in the analysis of criminalbehaviour and in the formalised probabilistic assessment of the risk of rape reoffending througha case study of a serial rapist sentenced to a long-term term of imprisonment. The study isgrounded in a Bayesian inferential framework, in which the recidivism hypothesis is operationalised as a binary outcome: the reoccurrence of rape within a three-year period following release(2029–2032). The individualised baseline probability (empirical prior) was estimated using abeta–binomial Bayesian model based on the offender’s criminal history, due to the absence ofdomestic longitudinal recidivism rates for the specified time horizon. The evidence used forBayesian updating comprised operationalised risk indicators, including repeated rape followingprevious releases, escalation of violence, the presence of antisocial personality disorder, impulsivity, and stable modus operandi patterns. Additional empirical data from a domestic studyon rape recidivism were used to contextualise the findings. The results of the Bayesian analysisindicate that the posterior probability of recidivism within the three-year period remains exceptionally high (≈0.97–0.99), even under conservative assumptions regarding evidential strength.The findings suggest that the potential protective effects of age and long-term imprisonment,even when considered under a conservative scenario, do not outweigh the strong pattern ofprior behaviour and the clinical-behavioural risk factors. In conclusion, the paper demonstratesthat Bayes’ theorem constitutes a methodologically transparent and practically applicableframework for individualised probabilistic reasoning in forensic risk assessment.

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