1. A method on a computer for aiding in the analysis of a legal matter using a decision tree and a Bayesian network, comprising: generating a decision tree representing relationships between a plurality of legal inquiries and a plurality of legal conclusions, wherein the decision tree comprises a plurality of nodes and a plurality of edges connecting the nodes, wherein each node is associated with a variable that represents either an answer to a legal inquiry or a legal conclusion, and an edge represents a conditional dependency between variables of nodes; generating a Bayesian network representing probabilistic relationships between a plurality of legal inquiries and a plurality of legal conclusions, wherein the Bayesian network comprises a plurality of nodes and a plurality of edges connecting the nodes, wherein each node is associated with a variable that represents either an answer to a legal inquiry or a legal conclusion, and an edge represents a conditional dependency between variables of nodes; associating a probability function with each node, wherein a probability function takes as input one or more values of variables from one or more parent nodes and gives a probability of a child node's variable; providing to a user, via a graphical user interface, the plurality of legal inquiries; receiving from the user, via the graphical user interface, answers to at least a portion of the legal inquiries; replacing a variable of each node of the decision tree corresponding to an answer provided by the user with a value representing the answer; replacing a variable of each node of the Bayesian network corresponding to an answer provided by the user with a value representing the answer; calculating a resulting legal conclusion via the decision tree based on the answers provided by the user; executing the probability function of each node of the Bayesian network, thereby calculating the probability of each legal conclusion based on the answers provided by the user; displaying for the user, via the graphical user interface, the legal conclusion calculated via the decision tree and the probability of each legal conclusion from the Bayesian network; storing a record associated with the user, including the legal conclusion calculated via the decision tree, the probability of each legal conclusion from the Bayesian network, the plurality of legal inquiries and the plurality of answers; receiving a legal update comprising a change in law that affects how the legal conclusions are reached in the decision tree and how the probability of each legal conclusion is reached in the Bayesian network; automatically identifying nodes, edges, legal inquiries or legal conclusions of the decision tree and the Bayesian network that must be modified in light of the legal update; automatically modifying the nodes, edges, legal inquiries or legal conclusions of the decision tree and the Bayesian network that were identified, in light of the legal update; replacing a variable of each node in the modified decision tree corresponding to an answer provided by the user with a value representing the answer; replacing a variable of each node in the modified Bayesian network corresponding to an answer provided by the user with a value representing the answer; re-calculating a resulting legal conclusion via the decision tree based on the answers provided by the user; executing the probability function of each node in the modified Bayesian network, thereby re-calculating the probability of each legal conclusion based on the answers provided by the user; and wherein if the legal conclusion in the modified decision tree does not match the legal conclusion in the record that was stored, or if the probability of each legal conclusion in the modified Bayesian network does not match the probability of each legal conclusion in the record that was stored, sending a message to the user.