Abstract: Systems for maintaining light sources for semiconductor photolithography in which a module making up part of the light source is evaluated at various pulse counts to produce a binary prediction as to whether the module is sufficiently likely to operate without failure in an ensuing sequence of pulses. The binary prediction may be made by a machine learning model trained on metrics extracted from measurements taken on deinstalled modules. A group of models, each trained differently, can be made available according to a selection made by the user or according to the maintenance objectives of the user.