We have developed a method for quantifying the complexity of activation patterns observed during ventricular fibrillation (VF) that is based on our previously reported methodology for decomposing epicardial mapping data into a set of isolated wavefronts. One-half second datasets are acquired from a 21 × 24 array of unipolar electrodes (1 mm spacing), and the wavefronts are isolated. A correlation technique is used to compute the similarity between all possible pairs of the isolated wavefronts. From these data, the wavefronts are sorted into clusters, each of which represents a recurring wavefront morphology. We define multiplicity (M) as the number of clusters needed to account for 90% of the total activations in the VF episode. M measures the complexity of the rhythm. In repetitive patterns (e.g., sinus rhythm), M = 1, indicating that the same morphology repeatedly activates the mapped region. Typically, in VF, M > 1, with larger numbers representing more complex, disorganized patterns. As an example, we computed M at 5,10,15, and 20 sec after electrical induction of VF in six pigs. M decreased significantly (p < 0.001). suggesting increasing organization during this period.