While there is a burgeoning body of research linking smoking during pregnancy to problem behaviour in offspring, a major criticism of this work has been the crude measurement of exposure in these studies (e.g. retrospective, self-reported only) that could lead to biased estimates. To address this issue, we used a pregnancy cohort with repeated prospective measures of exposure as well as biological assays to generate estimates of exposure patterns using a range of modelling techniques. In this paper we report on the analytical approaches we have developed, including patterns of exposure over time and best-estimate approaches that combine self-report and cotinine measures, and compare their predictive value in relation to different dimensions of fetal growth as a first step towards examining the utility of greater precision of exposure measurement. Surprisingly, in this sample the more complex assessments of exposure, including biological measures, generally did not perform better than simple indicators of exposure based on repeated self-report measures, with one exception: a combined self-report cotinine 'best estimate' of third trimester exposure was uniquely associated with lower brain : body ratio. Further study is needed using more sophisticated cotinine assays and testing prediction of a range of outcomes to ascertain whether these findings represent true differences or are specific to the sample, methods and outcomes used. Such research will inform the development of guidelines for adequate exposure characterisation in developmental studies.