In mechanical transmission systems, gears play a crucial role, necessitating the forecasting of their lifespan. Gears are susceptible to various modes of failure, including scuffing, scoring, and flank fracture, with pitting emerging as the most common issue. Pitting, a common form of gear damage, arises due to localized pressure and can significantly impact the gear's longevity. Specifically, the focus of this study is on predicting the fatigue life associated with pitting. Traditionally, standards like ISO and AGMA have provided models for calculating pitting stress to prevent such failures. The equations in these models establish stress limits and associated safety factors, but they do not directly address the estimation of the Remaining Useful Life (RUL). Furthermore, some existing fatigue life models for gears tend to focus heavily on the occurrence of significant spalling, a type of surface damage, while neglecting the percentage of the pitting area as a contributing factor. To address this limitation, this paper proposes a novel approach. It proposes a modified life predictive model resulting from the integration of an analytical gear L10 fatigue life model with experimental data obtained from tests involving alternating pitting stress and cycles, considering various percentages of pitting area. By incorporating the percentage of pitting area into the model, its predictive accuracy is significantly enhanced, offering a more comprehensive understanding of gear health and longevity. This modified model enables engineers and maintenance professionals to make more informed decisions regarding gear maintenance schedules and replacement strategies. Ultimately, it empowers them to predict the L10 life of a spur gear pair with greater precision, based on specific percentages of pitting area identified in real-world operating conditions.