Smoking is the leading cause of preventable death worldwide, causing 6 million deaths every year (WHO, 2011). Most people try smoking for the first time in adolescence (O’Loughlin et al., 2014), making this a critical period for research regarding risk factors for progressing into nicotine addiction. As with other substance use disorders, much is known about how nicotine-induced changes in neurotransmitter systems and sensitivity to drug- and non-drug rewards lead from recreational to habitual and finally to compulsive use. Differences in personality, life history, environment, behavioural responding, and neurobiology between non-smokers, smokers, and smokers who manage to quit are also known. However, there is very little evidence as to what pre-existing neurobiological factors make adolescents vulnerable to smoking behaviour. Using a large sample of 548 14-year old non-smokers, machine learning was used to predict smoking behaviour in the next four years.