Opportunistic communications through wireless ad-hoc mesh networks have been thoroughly studied in the context of military infrastructureless deployments, sensor networks and even human-centered pervasive networking. However, due to the lack of a model that accurately computes the probability distribution of the delay, we usually content ourselves with the mean values. Such an approach can limit both the ability to predict the system's behavior and the ways to affect it. In this paper, we present an analytical framework that allows us to estimate the probability distribution of the delay as a function of the field size, the number of participating users and the movement model. In addition, the short computational time, as compared to simulations, allows us to analyze systems that would otherwise be infeasible, due to their size. The derived delay probability distribution can help us decide whether opportunistic networking can be practically used in, e.g., dense vehicular environments, highly volatile mesh networks, or even predicting a successful marketing campaign. We validate the analytical results against a simulation of the presented model. Furthermore, we created a second, highly sophisticated and realistic, simulation, in order to verify the validity of the observed trends in almost-real-life situations.