Criminal analysis as a tool for increasing the efficiency of pre-trial investigation in cases of serious crimes

Main Article Content

Ihor Hradun

Abstract

The article examines the role of criminal analysis as a key tool for increasing the effectiveness of pre-trial investigation in cases of serious crimes. Modern approaches to the application of criminal analytical methods and technologies in the practice of law enforcement agencies are analyzed, in particular their importance for the systematization, interpretation and prediction of criminal activity. The author pays attention to the methodological foundations of criminal analysis, which provide a holistic view of the criminogenic situation, contribute to the identification of key factors and connections between subjects of criminal activity. An updated methodological model of criminal analysis is proposed, which integrates traditional analytical approaches with innovative information technologies, in particular big data and machine learning methods. The scientific novelty lies in the identification and systematization of key factors that affect the quality of operational and investigative activities, as well as in the development of practical recommendations for optimizing criminal analytical work in order to increase the accuracy of predicting criminal activity and the speed of solving serious crimes. Particular attention is paid to the problems of staffing and regulatory and legal regulation, which create obstacles to the effective integration of criminal analysis into pre-trial investigation. The results of the study can be implemented in the practice of law enforcement agencies to increase the effectiveness of the fight against crime, and will also become the basis for further scientific developments in the field of criminal analysis. The article also examines the problems and challenges that arise when integrating criminal analysis into pre-trial investigation, in particular the lack of human resources and the need to implement modern information systems. Practical recommendations are aimed at improving regulatory and legal regulation and improving the skills of analytical workers. The results of the study can be useful for scientists, practitioners of law enforcement agencies and judicial authorities.

Article Details

Section

ARTICLES

How to Cite

Criminal analysis as a tool for increasing the efficiency of pre-trial investigation in cases of serious crimes. (2026). LEGAL HORIZONS, 28(1), 72-80. https://doi.org/10.54477/LH.25192353.2026.1.pp.72-80

References

Abrams, G. (2024). Artificial intelligence is revolutionizing criminal profiling and investigation. Journal of Forensic Medicine, 9, 355. https://doi.org/10.37421/2472-1026.2024.9.355

Boba Santos, R. (2013). Crime analysis with crime mapping (3rd ed.). Sage Publications.

Brown, E., & Ballucci, D. (2022). Understanding crime analyst’s roles and responsibilities and the impact of their work. Policing and Society. https://doi.org/10.1177/17488958221095980

Canter, D. (2004). Offender profiling and investigative psychology. Journal of Investigative Psychology and Offender Profiling, 1(1), 1–15. https://doi.org/10.1002/jip.7

Chamard, S. (2006). The history of crime mapping and its use by American police departments. Alaska Justice Forum, 23(3), 1–9.

Cope, N. (2004). Intelligence led policing or policing led intelligence? British Journal of Criminology, 44(2), 188–203. DOI: https://doi.org/10.1093/bjc/44.2.188

Innes, M., Fielding, N., & Cope, N. (2005). The appliance of science? The theory and practice of crime intelligence analysis. British Journal of Criminology, 45(1), 39–57.DOI: https://doi.org/10.1093/bjc/azh053

Innes, M., Fielding, N., & Cope, N. (2005). The appliance of science? The theory and practice of crime intelligence analysis. British Journal of Criminology, 45(1), 39–57. https://doi.org/10.1093/bjc/azh053

Khalfa, R., & Hardyns, W. (2024). Led by intelligence: A scoping review on the experimental evaluation of intelligence-led policing. Evaluation Review, 48(5). https://doi.org/10.1177/0193841X231204588

Maoro, F., & Geierhos, M. (2025). Contestable AI for criminal intelligence analysis: Improving decision-making through semantic modeling and human oversight. Frontiers in Artificial Intelligence, 8. https://doi.org/10.3389/frai.2025.1602998

McCue, C. (2015). Data mining and predictive analysis: Intelligence gathering and crime analysis (2nd ed.). Butterworth-Heinemann.

Mohler, G. O., Short, M. B., Brantingham, P. J., Schoenberg, F. P., & Tita, G. E. (2011). Self-exciting point process modeling of crime. Journal of the American Statistical Association, 106(493), 100–108. DOI: https://doi.org/10.1198/jasa.2011.ap09546

Perry, W. L., McInnis, B., Price, C. C., Smith, S. C., & Hollywood, J. S. (2013). Predictive Policing. RAND Corporation. DOI: https://doi.org/10.7249/RR233

Perry, W. L., McInnis, B., Price, C. C., Smith, S. C., & Hollywood, J. S. (2013). Predictive policing: The role of crime forecasting in law enforcement operations. RAND Corporation. https://doi.org/10.7249/RR233

Piza, E. L., & Arietti, R. A. (2022). Crime analysis in policing. Oxford Research Encyclopedia of Criminology and Criminal Justice. https://doi.org/10.1093/acrefore/9780190264079.013.716

Ratcliffe, J. H. (2016). Intelligence-Led Policing (2nd ed.). Routledge.

DOI: https://doi.org/10.4324/9781315721743

Ratcliffe, J. H. (2016). Intelligence-led policing (2nd ed.). Routledge.

Turet, J. G., & Seixas Costa, A. P. C. (2022). Hybrid methodology for analysis of structured and unstruc-tured data to support decision-making in public security. Data & Knowledge Engineering, 141. https://doi.org/10.1016/j.datak.2022.102056