OBJECTIVES: Several genetic characteristics are implicated in the onset of lung cancer and the smoking-gene interaction means that some smokers are at greater risk of developing lung cancer than others.  The purpose of this study was to explore the potential cost-effectiveness of offering smokers a genetic test designed to provide feedback regarding their individual risk of developing lung cancer to motivate smoking cessation. METHODS: Two strategies were modelled; heavy-smoking individuals aged 50 years either received or did not receive a genetic test within the course of a usual smoking-cessation intervention comprising nicotine replacement therapy (NRT) and counselling.   A Markov model was constructed using evidence from published randomized controlled trials and meta-analyses for estimates on 12-month quit rates and long-term relapse rates.  Recent epidemiological data were used for estimates on the risk of developing lung cancer stratified by time since quitting and heavy/light smoking patterns.  Scenario analyses, one-way and probabilistic sensitivity analyses were used to explore uncertainty. RESULTS: The discounted incremental costs for the genetic testing strategy were AU$299 and corresponding quality-adjusted life years (QALYs) were 0.0109 producing an incremental cost per QALY of AUS$34,687 (95% CI $12,483, $87,734).  At a willingness-to-pay of AU$20,000 per QALY gained, the genetic testing strategy needs to have a minimum 12-month quit rate of 12.4% or the relapse rate 12% lower to demonstrate cost-effective equivalence to NRT and counselling alone. The probability that adding a genetic test to the usual smoking-cessation intervention is cost-effective was 20.6%. CONCLUSIONS: Very small differences in costs and QALYs were found between the two options over a period of 35 years.  The findings were sensitive to small changes in critical variables such as the 12-month quit rates and relapse rates.  Further research on smoking-cessation quit rates following genetic testing is needed to inform cost-utility analyses.