Tobacco use is prevalent in adolescents and understanding factors that contribute to smoking uptake remains a critical public health priority. While there is now good support for the role of implicit (preconscious) cognitive processing in accounting for changes in drug use, these models have not been applied to tobacco use. Longitudinal analysis of smoking data presents unique problems, because these data are usually highly positively skewed (with excess zeros) and render conventional statistical tools (e.g., OLS regression) largely inappropriate. This study advanced the application of implicit memory theory to adolescent smoking by adopting statistical methods that do not rely on assumptions of normality, and produce robust estimates from data with correlated observations. The study examined the longitudinal association of implicit tobacco-related memory associations (TMAs) and smoking in 114 Australian high school students. Participants completed TMA tasks and behavioural checklists designed to obscure the tobacco-related focus of the study. Results showed that the TMA-smoking association remained significant when accounting for within-subject variability, and TMAs at Time 1 were modestly associated with smoking at Time 2 after accounting for within subject variability. Students with stronger preconscious smoking-related associations appear to be at greater risk of smoking. Strategies that target implicit TMAs may be an effective early intervention or prevention tool. The statistical method will be of use in future research on adolescent smoking, and for research on other behavioural distributions that are highly positively skewed.