The efficient assignment of lecturers to courses is vital in Higher Education Institutions to ensure both faculty satisfaction and optimal course delivery. This paper proposes a Modified Hungarian Method (MHM) optimization model for the assignment of lecturer-to-course considering their competency and preference scores. Previous research predominantly employed the Hungarian method, with a limited exploration of the MHM optimization model. Furthermore, the combination of competency and preference-based lecturer-to-course has never been applied. To enhance the formulation of the MHM model, this study presents a mathematical programming approach. The objective of this study is to maximize overall competency and preferences based MHM (CP-MHM) model in lecturer-to-course assignments. Competency and preferences data from Mathematics lecturers at UiTM Shah Alam, Malaysia were gathered via an online survey for undergraduate courses. Using these competency and preference scores as input, the CP-MHM model was implemented using MATLAB’s intlinprog to produce an optimal assignment plan, restricting lecturers to a maximum of three courses. The optimal solutions of the CP-MHM model indicate which courses are best assigned to a particular lecturer, based on their competency and preference scores. The competency levels are assessed using three factors namely knowledge, skills, and teaching motivation. This research improves educational planning by providing a useful tool for assigning lecturers to courses in real-world situations. The main contribution of our study is adapting the MHM optimization model to efficiently integrate lecturers’ competency and preference levels and other multidimensional inputs. The model aims to improve teaching quality, minimize mismatches, and boost overall academic performance.