This study provides insights into the effectiveness of the genetic algorithm-based optimization process for long-short addendum helical gear pairs, aiming to balance the specific sliding ratio during approach and recess phases while concurrently increasing the load-carrying capacity to the pinion. The iterative process, undertaken with an appropriately chosen population size for the two variables (x1 and x2) over the specified maximum number of generations, consistently yields reliable results, highlighting the algorithm's efficiency and convergence. Visual representations highlight significant addendum modifications, showcasing the algorithm's adaptability to meet specific design criteria for long-short addendum helical gear pairs. The study further explores the reduction in tooth root stress and contact stress of standard helical gears after optimization, determined through finite element analysis using ANSYS software. Additionally, the effects of addendum modification on helix angle and total volume of the gear are examined in detail. A numerical approach is established to calculate the cross-sectional area of the single helical gear tooth in the transverse plane and the total volume of the gear for both standard and optimized long-short addendum helical gears. This approach is validated with real-time CAD models, confirming its accuracy by yielding identical values. In summary, the research underscores the effectiveness of the genetic algorithm-based optimization process for long-short addendum helical gear pairs, with a dual focus on balancing specific sliding ratios and increasing the load-carrying capacity to the pinion, offering valuable insights for advancing such gear configurations in engineering applications.