In the first part of the talk, mainly of the heuristic type, some basic notions (such as regularity, properness, disintegrability) are recalled and some examples are discussed. The second part is more technical and is devoted to some results and their implications. In the classical (Kolmogorovian) framework, a few 0-1 laws for regular conditional distributions are stated. Special attention is paid to the tail and the symmetric sigma- fields. In the coherent (de Finettian) framework, with reference to a Bayesian inferential problem, the existence of posterior distributions that make sufficient a given statistics, or make optimal a given estimator, is discussed. Finally, some compatibility problems for conditional distributions are mentioned, and a few asymptotic results are stated