PURPOSES: The purpose of this study is to identify the key factors that influence a driver’s trust in road-freezing risk information METHODS : A survey was designed and conducted in the metropolitan area to analyze drivers’perception towards road-freezing risk information. A binary logistic regression model was developed based on the survey responses. The statistically significant model coefficients were determined and their odds ratios were calculated. Finally, they were considered as the key factors influencing drivers’trust in roadfreezing risk information. RESULTS : The developed binary logistic regression model was validated through statistical tests. The final results indicated that previous experiences of accidents on slippery roads, as well as route choice patterns are statistically significant, having 95% confidence levels. CONCLUSIONS : Previous experiences of accidents on slippery roads and road choice patterns are the factors that most significantly influence drivers’trust in road-freezing risk information. The findings of this study will be used as fundamental data in establishing tailored road-freezing risk mitigation procedures and services.