Aircraft maintenance safety is critically influenced by human and organizational factors, yet maintenance errors continue to represent a significant risk within aviation operations. This study investigates the influence of human performance factors, organizational conditions, and operational pressures on aircraft maintenance errors using an integrated analytical approach. The research adopts a mixed-methods design combining quantitative survey data with qualitative insights from maintenance professionals. Data were collected from 120 aircraft maintenance personnel, including technicians, supervisors, and safety managers, through structured questionnaires, interviews, and analysis of maintenance reports. Statistical analysis was conducted using descriptive statistics, correlation analysis, multiple regression, and chi-square testing to examine relationships between key variables such as human factors awareness, training adequacy, communication effectiveness, workload and fatigue, and organizational safety culture. The findings indicate that workload and fatigue are the strongest predictors of maintenance errors (β = 0.35, p < 0.001), while human factors awareness (β = −0.31, p < 0.001) and organizational safety culture (β = −0.28, p = 0.001) significantly reduce error occurrence. Correlation results further demonstrate that maintenance errors are positively associated with workload and fatigue (r = 0.49) and negatively associated with safety culture (r = −0.57). Additionally, chi-square analysis reveals a significant relationship between training levels and maintenance error reporting (χ² = 14.27, p = 0.001). The study concludes that aircraft maintenance errors arise from the interaction of human, organizational, and operational factors rather than isolated individual failures. Strengthening human factors training, improving communication procedures, implementing fatigue risk management systems, and promoting a proactive safety culture are essential for enhancing maintenance safety. The research contributes to aviation safety literature by providing empirical evidence supporting integrated human–system approaches to maintenance error prevention.