Probabilistic reasoning is a key aspect of artificial intelligence. In this talk we will look at probabilistic reasoning through the lens of ProbLog, a probabilistic logic programming language. This language extends the logical facts and rules of Prolog with probabilistic facts. Probabilistic reasoning in this language is achieved through knowledge compilation techniques. We will delve deeper into the details of this reasoning pipeline and highlight some of ProbLog's extensions. In particular we consider DeepProbLog, which heavily benefits from inference through d-DNNF compilation. DeepProbLog is positioned within the domain of neurosymbolic AI, a promising field of AI where symbolic and subsymbolic reasoning coexist.