Alzheimer's disease (AD) is a chronic and progressive neurodegenerative disease characterized by a progressive deterioration in cognitive functions. AD will have a major impact on public health in the coming decades. The objective of this study was to evaluate the potential cost-effectiveness of a cognitive-behavioral family intervention (CBFI) program in patients with mild Alzheimer's disease in Finland. A second-order Monte Carlo technique was used to simulate the effectiveness of the intervention in AD patients and their informal caregivers over the course of 5 years. A Bayesian approach was applied to answer the question: how likely is it that the CBFI program is cost-effective? Based on existing information, the incremental net health benefit of the CBFI program is positive with over 0.9 probability, which indicates that the CBFI program has the highest probability of being optimal by providing greater net benefits than current practice. Furthermore, changes in the health-related quality of life of the caregivers were insensitive to AD patients' disease stage and settings of care. From the methodological point of view, the acceptability curve with a Bayesian approach provides a flexible way to characterize uncertainty surrounding cost-effectiveness parameters.