In the landscape of breast cancer, which affects around ten percent of women worldwide, the precise alignment of breast MRI images is of utmost significance. This alignment enhances the ability to compare pre- and post-contrast pictures, which helps in accurately diagnosing and categorizing cancer types as either benign or malignant using pharmacokinetic analysis. Furthermore, it allows for the identification and separation of abnormalities that occur at various time intervals, which is crucial for the successful tracking of cancer treatments. Historically, image registration approaches heavily depended on control points and used semi-automated procedures. A shift in focus, however, has been toward more sophisticated voxel-based automated systems that rely heavily on mutual information to determine how similar two objects are. This publication proposes the use of the Whale Optimization technique (WOA) for breast MRI registration. WOA is a metaheuristics-based optimization technique that has been used to register breast MR images. We have analyzed a total of 25 sets of breast MR images taken before and after the administration of a contrast agent. The results suggest that the WOA-based registration strategy is superior to commonly used approaches such as Particle Swarm Optimization (PSO), Gorilla Troop Optimization (GTO), and Arithmetic Optimization Algorithm (AOA). According to the experimental findings, the registration method that utilizes WOA (Whale Optimization Algorithm) works better than the registration methods that use PSO (Particle Swarm Optimization), GTO (Gorilla Troop Optimization), and AOA (Arithmetic Optimization Algorithm) when it comes to aligning breast MR images. This discrepancy is statistically significant.