The level of sophistication reached by today's Si device fabrication technologies has called for new modeling and simulation schemes, capable of handling the wide variety of interaction mechanisms that govern the complex phenomena that can occur at the atomic level. The kinetic Monte Carlo (KMC) technique seems particularly apt for this task. It takes as input basic materials parameters, derived from ab-initio calculations or from experiments, and is capable of carrying out a detailed simulation up to the dimensions and time scales of current ULSI Si device manufacture. In addition, it can accommodate and efficiently simulate complex interactions between multiple dopant and defect types. We explain the approach and show examples of application in both materials processing and device fabrication. Finally, we present the use of some artificial intelligence techniques (namely, genetic algorithms) that look most promising as methodologies that can easy and efficiently be employed to build the extensive KMC parameter database.