As alternative transportation is getting more and more fashionable, and more people worldwide are 'shifting' to walking trips, even for their daily commuting, traffic crashes suffered by pedestrians are still a great concern for road safety and public health researchers and practitioners. In this regard, risky or 'aberrant' road behaviors have emerged, during the last few years, as a key issue to be considered for crash prevention. Nevertheless, the idea of a 'generic pedestrian' is getting re-evaluated, and analyzing key features, such as gender, seems to be crucial for understanding pedestrians' performance and safety outcomes. Objective: The objective of this study was to examine the effect of gender on pedestrians' both deliberate (traffic violations) and undeliberate (errors) risky walking behaviors, considering a set of theoretically based demographic and psychosocial variables as their potential predictors. Method: For this cross-sectional study, data from 1070 Spanish pedestrians (60 % females and 40 % males, aged between 16 and 79) from the 17 regions of Spain, responding to an electronic questionnaire, were analyzed through a multi-group structural equation modeling (MGSEM) approach. Results: Although age, handheld device-interaction, and sensation-seeking seem to have a similar effect on the errors and violations reported by both genders (similarities), factors such as risk perception, educational level and the misbehaviors observed in other road users are significant predictors only in the case of male pedestrians. On the other hand, road distractions have been shown to play a significant role in females' errors and violations, while males' road distractions seem to only affect their involuntary risky behaviors. Conclusion: The findings of this study support the influence of gender in the statistical explanation of both deliberate and undeliberate walking risky road behaviors, also depicting the differential role of certain demographic and psychosocial factors when we compare male and female pedestrians.