The heart characteristic length, the inverse of conduction velocity (CV), and the inverse of the refractory period are known to determine vulnerability to cardiac fibrillation (fibrillation number, FibN) in in silico or ex vivo models. The purpose of this study was to validate the accuracy of FibN through in silico atrial modeling and to evaluate its clinical application in patients with atrial fibrillation (AF) who had undergone radiofrequency catheter ablation. We compared the maintenance duration of AF at various FibNAF values using in silico bidomain atrial modeling. Among 60 patients (72% male, 54 ± 13 years old, 82% with paroxysmal AF) who underwent circumferential pulmonary vein isolation (CPVI) for AF rhythm control, we examined the relationship between FibNAF and postprocedural AF inducibility or induction pacing cycle length (iPCL). Clinical FibNAF was calculated using left atrium (LA) dimension (echocardiogram), the inverse of CV, and the inverse of the atrial effective refractory periods measured at proximal and distal coronary sinus. In silico simulation found a positive correlation between AF maintenance duration and FibN_AF (R = 0.90, p <; 0.001). After clinical CPVI, FibN_AF (0.296 ± 0.038 versus 0.192 ± 0.028, p <; 0.001) was significantly higher in patients with postprocedural AF inducibility (n = 41) than in those without (n = 19). Among 41 patients with postprocedural AF inducibility, FibN_AF (P = 0.935, p <; 0.001) had excellent correlations with induction pacing cycle length. FibN_AF, based on LA mass and wavelength, correlates well with AF maintenance in computational modeling and clinical AF inducibility after CPVI.