  In this paper, we apply the Stein's method in the context of point processes,
namely when the target measure is the distribution of a finite Poisson point
process. We show that the so-called Kantorovich-Rubinstein distance between
such a measure and another finite point process is bounded by the
$L^1$-distance between their respective Papangelou intensities. Then, we deduce
some convergence rates for sequences of point processes approaching a Poisson
or a Cox point process.
