The ability to identify factors that influence serious injuries and fatalities would help construction firms triage hazardous situations and direct their resources towards more effective interventions . Therefore, this study used odds ratio analysis and logistic regression modeling on historical accident data to investigate the contributing factors impacting occupational accidents among small electrical contracting enterprises . After conducting a thorough content analysis to ensure the reliability of reports, the authors adopted a purposeful variable selection approach to determine the most significant factors that can explain the fatality rates in different scenarios . Thereafter, this study performed an odds ratio analysis among significant factors to determine which factors increase the likelihood of fatality . For example, it was found that having a fatal accident is 4.4 times more likely when the source is a``vehicle"than when it is a``tool, instrument, or equipment". After validating the consistency of the model , 105 accident scenarios were developed and assessed using the model . The findings revealed which severe accident scenarios happen commonly to people in this trade, with nine scenarios having fatality rates of 50% or more . The highest fatality rates occurred in``fencing, installing lights, signs, etc ."tasks in``alteration and rehabilitation"projects where the source of injury was``parts and materials". The proposed analysis/modeling approach can be applied among all specialty contracting companies to identify and prioritize more hazardous situations within specific trades . The proposed model-development process also contributes to the body of knowledge around accident analysis by providing a framework for analyzing accident reports through a multivariate logistic regression model.