1. An apparatus for making a probabilistic inference based on a belief network including a child node Y and one or more parent nodes X i (i=1,. .. , n) for the child node Y, the apparatus comprising: a processing system configured to receive as input one or more parameters of a causal influence model that describes influence of the parent nodes X i on possible states of the child node Y, the processing system further configured to convert the parameters of the causal influence model into one or more entries of a conditional probability table, using a creation function; wherein the conditional probability table provides a probability distribution for all the possible states of the child node Y, for each combination of possible states of the parent nodes X i .