Cognitive science is a very active field of scientific interest. It turns out to be a "melting pot" of ideas coming from very different areas. One of the principal hopes is that some synthetic cognitive paradigms will emerge from this interdisciplinary "brain storming". The goal of this paper is to answer the question: "Given the state of the art, is there any hints indicating the emergence of such synthetic paradigms?" The main thesis of the paper is that there is a good candidate, namely, the probabilistic inference paradigm. In support of the above thesis the structure of the paper is as follows: - in a first part, we identify five criteria to qualify as a synthetic cognitive paradigm (validity, self consistency, competence, feasibility and mimetic power) - in the second paragraph, the principles of probabilistic inference are reviewed and justifications of validity and self consistency of this paradigm are given (Marr's computational level) - then, the competence criterion is discussed, considering the efficiency of probabilistic inference for dealing with the different classical cognitive riddles and analyzing the relationships of probabilistic inference with several of the usual connexionist formalisms (Marr's algorithmic level) - the criteria of feasibility (condition of computer implementation) and mimetic power (adequation with what is known of the architecture of the nervous system) are finally considered in the fourth part (Marr's implementation level). As a conclusion, it will appear that the probabilistic inference is at least a very interesting framework to get a synthetic overview of a number of works in the area and to identify and formalize the most puzzling questions. Some of these questions will be listed. In fact, probabilistic inference will appear finally to be able to play the same role for computational cognitive science that formal logic has played for classical symbolic Artificial Intelligence: a sound mathematical foundation serving as a guide line, as a constant reference and as a source of inspiration.