The aims of this study were to 1) develop a detection model for recognizing panic disorder (PD), 2) develop a simple questionnaire as a screening instrument for PD detection, and 3) test in an outpatient cardiological chest pain population a detection model for panic disorder previously described by Fleet et al. [20]. Logistic regression analysis was performed to explore factors predictive of panic disorder and to test the cross-cardiological setting constancy of the Fleet model in 199 chest pain patients without previously known heart disease referred to cardiological outpatient investigation of chest pain. The SCL-90 somatization subscale, Agoraphobia Cognitions Questionnaire, chest pain quality, pain localization, and age were the best predictors of the presence of panic disorder. This model correctly classified 78% of the subjects. The sum-score of a three-item questionnaire correctly classified 74% of the subjects, while the previously described model by Fleet et al. correctly classified 73% of the subjects. A detection model and a screening questionnaire are proposed to improve the recognition of PD in this chest pain population. This study partly supports the cross-setting validity of a previously described detection model.