Conservation planning decisions are essential to preserve biodiversity. However, these decisions are complex due to their multiple attributes which may overload computational solvers. This requires planners to use heuristic procedures that may provide sub-optimal solutions. The aim of this project is to develop a decision planning tool that leverages existing landscape attributes to recommend which patches to protect by using mathematical optimization. To reduce the number of possible options, the set of patches in the landscape will be run through a preprocessing phase before conducting optimization. Finally, the tool will be tested using data from a real landscape.