Background: The need to understand and respond to the unique characteristics and drivers of suicidal behaviour in rural areas has been enabled through the Australian Government’s 2015 mental health reforms facilitating a move to an evidence-based, regional approach to suicide prevention. However, a key challenge has been the complex decision-making environment and lack of appropriate tools to facilitate the use of evidence, data and expert knowledge in a way that can inform contextually appropriate strategies that will deliver the greatest impact. This paper reports the co-development of an advanced decision support tool that enables regional decision makers to explore the likely impacts of their decisions before implementing them in the real world. Methods: A system dynamics model for the rural and remote population catchment of Western New South Wales was developed. The model was based on defined pathways to mental health care and suicidal behaviour and reproduced historic trends in the incidence of attempted suicide (self-harm hospitalisations) and suicide deaths in the region. A series of intervention scenarios were investigated to forecast their impact on suicidal behaviour over a 10-year period. Results: Post-suicide attempt assertive aftercare was forecast to deliver the greatest impact, reducing the numbers of self-harm hospitalisations and suicide deaths by 5.65% (95% interval, 4.87−6.42%) and 5.45% (4.68−6.22%), respectively. Reductions were also projected for community support programs (self-harm hospitalisations: 2.83%, 95% interval 2.23−3.46%; suicide deaths: 4.38%, 95% interval 3.78−5.00%). Some scenarios produced unintuitive impacts or effect sizes that were significantly lower than what has been anticipated under the traditional evidence-based approach to suicide prevention and provide an opportunity for learning. Conclusion: Systems modelling and simulation offers significant potential for regional decision makers to better understand and respond to the unique characteristics and drivers of suicidal behaviour in their catchments and more effectively allocate limited health resources.