One important aspect of the seismicity is the spatiotemporal clustering; hence, the distinction between independent and triggered events is a critical part of the analysis of seismic catalogs. Stochastic declustering of seismicity allows a probabilistic distinction between these two kinds of events. Such an approach, usually performed with the epidemic‐type aftershock sequence (ETAS) model, avoids the bias in the estimation of the frequency–magnitude distribution parameters if we consider a subset of the catalog, that is, only the independent or the triggered events. In this article, we present a framework to properly include the probabilities of any event to be independent (or triggered) both in the temporal variation of the seismic rates and in the estimation of the b‐value of the Gutenberg–Richter law. This framework is then applied to a high‐definition seismic catalog in the central part of Italy covering the period from April 2010 to December 2015. The results of our analysis show that the seismic activity from the beginning of the catalog to March 2013 is characterized by a low degree of clustering and a relatively high b‐value, whereas the following period exhibits a higher degree of clustering and a smaller b‐value.