This project aims to automate the allocation of classrooms for the disciplines at the Pontifical Catholic University of Rio de Janeiro (PUC-Rio). The motivation for developing this system arises from the complexity and workload involved in the current manual process carried out by the departments and the Central Graduation Coordination (CCG), which needs to allocate approximately 4500 disciplines each semester. This manual process is repetitive, error-prone, and consumes a considerable amount of the professionals time, negatively impacting the efficiency and accuracy of classroom allocation. The software developed in Python uses Genetic Algorithms (GA), an Artificial Intelligence metaheuristic, to find an optimized allocation, taking into account the requirements and preferences of each discipline, such as the number of offered seats and preferred buildings and floors. The use of GA in the developed software is a strategic choice, as this optimization technique can handle multiple constraints and preferences simultaneously. This includes considering the number of seats offered by each discipline, preferences for specific buildings and floors, and the need for additional resources in the rooms, such as computers. The advantages of automating this process are numerous. Firstly, efficiency is significantly increased, freeing the departments and CCG from the burden of manual work and allowing these human resources to be allocated to more strategic and intellectually challenging tasks. Secondly, the accuracy of classroom allocation is enhanced, as the algorithm can consider a greater number of variables, which would be impractical manually. The developed system is implemented in Python and can be run on web servers, accessible through any browser. The software can perform the allocation in either a full or partial manner, adapting to the specific needs of the departments. Tests conducted with real data from previous semesters demonstrate that the system meets the expectations of the departments and CCG, providing an efficient and accurate solution to the problem of classroom allocation.