This paper presents an integrated framework for climate change adaptation (CCA) planning by employing a stepwise process which consists of different analysis and modelling approaches. The key for success in the modelling phase is the integration of multidisciplinary assessments by coupling two approaches; Bayesian Networks (BNs) and System Dynamics (SD) in the context of climate change. Both BNs and SD have their particular benefits and limitations, and integrating these modelling tools can maximise their respective advantages by covering the otherís limitations. Specifically, SD is an apt approach to understand the nonlinear behaviour of complex systems, but not successful and effective in the treatment of uncertainty. Similarly, BNs are known as probabilistic and participatory tools that are capable of dealing with both quantitative and qualitative data, but conversely are unable to capture feedbacks within a dynamic system. Moreover, CCA has a number of dimensions and requirements that need to be addressed in the process of vulnerability assessment and planning. Adaptation plans are characteristically developed for systems that are uncertain, complex, and temporal, and which are changing over time. Additionally, the inclusion of stakeholder engagement and multidisciplinary expertise at relevant CCA planning stages is an essential requirement. Thus, the application of BN-SD coupling within a holistic framework is an effective approach leading to a successful CCA planning