1. A process for determining the occurrence and location of a boiler tube leak event in industrial boilers, said method having, as its principal object the effecting of such determination during the early initiation of such leak event, said method comprising: (a) determining for said boiler, a set of tube universal leak sensitive variables (ULSV); (b) calibrating the relationship between teaching data consisting of a plurality of known output patterns for each of said ULSVs in said set determined in step (a), supra, and learning sample data consisting of a plurality of sample patterns obtained from actual boiler tube leak events, or simulated boiler tube leak events, or both, by training a universal leak detection system (ULDS) Artificial Neural Network (ANN) by supplying said learning data thereto and comparing same with the corresponding teaching data patterns to thereby achieve a predetermined degree of convergence towards maximum pattern learning recognition; (c) determining for said boiler, a set of tube local leak sensitive variables (LLSV); (d) for each individual tube LLSV of the set determined in step (c), supra, calibrating the relationship between teaching data consisting of a plurality of known output patterns for each said individual LLSVs and learning sample data consisting of a plurality of sample patterns obtained from actual boiler tube leak events, or simulated boiler tube leak events, or both, by training, for each such LLSV, a corresponding ANN by supplying said learning data thereto and comparing same with the corresponding teaching data patterns to thereby achieve a predetermined degree of convergence towards maximum pattern learning recognition; (e) thereafter monitoring said industrial boiler for the occurrence of a leak event by observing changes in values in said boiler for each of said ULSVs and supplying said observed changes in values to said ULDS ANN for calculating a possibility that a leak event is occurring; (f) comparing the possibility calculated in step (e), supra, to a predetermined confidence threshold; (g) if the possibility compared in step (f), supra, is greater than said confidence threshold, concluding that a leak event is occurring and thereafter observing changes in values from said boiler for each of said LLSVs and supplying said observed changes in values to each of said corresponding local leak detection system (LLDS) ANNs for simultaneously calculating a possibility that the leak event is occurring at the location corresponding to one of said LLSVs; and (h) comparing each possibility calculated by each LLDS ANN in step (g), supra, one with the other, and concluding from said comparisons the location, in said boiler, of said leak event.