This paper addresses the question: Why and where do immigrants cluster? We examine the relative importance and interaction of two alternative explanations of immigrant clustering: (1) network externalities and (2) herd behavior. We advance the theory by presenting a framework encompassing both network and herd effects, and by delineating various types of network and herd effects in our empirical work. In order to distinguish between herd and network externalities, we use the Mexican Migration Project data. Our empirical results show that both network externalities and herds have significant effects on the migrant’s decision of where to migrate. Moreover, the significance and size of the effects vary according to the legal status of the migrant and whether the migrant is a “new” or a “repeat” migrant. The network-externality effect has an inverse U shape, not simply a linear positive effect as often presented in the literature. Neglecting herds and/or networks, or the inverse U shape of network effects leads to faulty conclusions about migrant behavior.