This research is concerned with the Malliavin-Stein approach, which combines Stein’s method for probabilistic approximation with infinite-dimensional integration by parts formulae based on Malliavin-type operators. We exploit it in many situations, such as density estimates, universality results, stochastic geometry, nodal statistics of random waves and more recently machine learning