Determining appropriate indoor temperature ranges and occupant’s optimal clothing insulation levels for building occupants is complex due to environmental and human factors. This study uses SVM and SVR models to predict temperature ranges and clothing insulation respectively, with a focus on gender differences. The SVM model shows better performance for females, with higher precision, recall, accuracy, and F1-scores, while the greater variability in male responses reduces performance. The SVR model reveals lower prediction errors and higher correlation for males in estimating insulation. These findings highlight the importance of gender-specific considerations for personalized comfort strategies and energy efficiency optimization.