The aim of the present paper is to construct a stochastic process, whose law is the solution of the Smoluchowski's coagulation equation. We introduce first a modified equation, dealing with the evolution of the distribu-tion Q t (dx) of the mass in the system. The advantage we take on this is that we can perform an unified study for both continuous and discrete models. The integro-partial-differential equation satisfied by {Q t } t ≥0 can be interpreted as the evolution equation of the time marginals of a Markov pure jump process. At this end we introduce a nonlinear Poisson driven stochastic differential equation related to the Smoluchowski equation in the following way: if X t satisfies this stochastic equation, then the law of X t satisfies the modified Smoluchowski equation. The nonlinear process is richer than the Smoluchowski equation, since it provides historical information on the particles. Existence, uniqueness and pathwise behavior for the solution of this SDE are studied. Finally, we prove that the nonlinear process X can be obtained as the limit of a Marcus–Lushnikov procedure. 1. Introduction. The coagulation model governs various phenomena as for example: polymerization, aggregation of colloidal particles, formation of stars and planets, behavior of fuel mixtures in engines, etc. Smoluchowski's coagulation equation models the dynamic of such phenomena and describes the evolution of a system of clusters which coalesce in order to form bigger clusters. Each cluster is identified by its size. The only mechanism taken into account is the coalescence of two clusters, other effects as multiple coagulation are neglected. We assume also that the rate of these reactions depends on the sizes of clusters involved in the coagulation. Denoting by n(k, t) the (nonnegative) concentration of clusters of size k at time t, the discrete