Background and Objective: Growing evidence shows that certain acute exposures, especially alcohol, may trigger episodes of paroxysmal atrial fibrillation (AF). However, there is a lack of methods for assessing the relation between triggers and AF episodes in individual patients. The present paper proposes an approach to identifying AF triggers based on the assumption that the post-trigger AF burden is larger than the pre-trigger AF burden during the analysis time interval. Method: For the purpose of identification, a measure of relational strength between pre- and post-trigger burden is introduced, accounting for the cumulative effect of the triggers contained in the observation interval. The proposed approach is explored for different types of AF episode pattern, generated using the alternating, bivariate Hawkes model, whose conditional intensity function is designed to account for the effect of alcohol. In total, 7200 different AF patterns were generated for different numbers of AF triggers and alcohol units. Results: The simulation study demonstrates that, depending on the pattern type, the relational strength increases 3–6 times with alcohol consumption in comparison with no consumption. Conclusions: The proposed approach to identifying triggers in individual patients with paroxysmal AF should facilitate the implementation of longitudinal studies for the objective assessment of trigger effect on AF occurrence.