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Bullying is a significant social and behavioural issue that affects the psychological, emotional, and social well-being of adolescents. Understanding the factors that contribute to bullying behaviour is essential in developing effective prevention strategies. This study proposes a Hierarchical Fuzzy Logic Control System (HFLC) to assess the tendency of individuals to engage in bullying behaviour by considering both peer and family dynamics. Five criteria were identified as key influencing factors: number of friends, frequency of quarrels with friends, time spent with friends outside school hours, parental knowledge of a child’s whereabouts, and frequency of intense arguments between parents. These criteria were organised into two subsystems, namely the peer factor subsystem and the family factor subsystem, which were implemented using MATLAB fuzzy inference systems. The outputs from these subsystems were then integrated into a main fuzzy system to determine the overall tendency of an individual to bully. The Mamdani fuzzy inference approach was applied through the stages of fuzzification, inference, composition, and defuzzification to generate interpretable results. The system classified individuals into three alternatives: more likely to bully, can be prevented, and not into bullying. Simulation results indicated that the category “can be prevented” achieved the highest score of 59.2, suggesting that bullying tendencies can be effectively reduced through appropriate interventions such as parental supervision and improved peer relationships. The findings demonstrate that the proposed HFLC model provides a structured and effective decision-support tool for analysing bullying behaviour under uncertainty. This approach highlights the usefulness of fuzzy logic in modelling complex social problems and offers valuable insights for educators, parents, and policymakers in developing preventive strategies against bullying.