Travel time variability (TTV) is a critical aspect of transportation studies, reflecting the fluctuations in travel time that vehicles experience on road networks. Understanding these variations and their underlying causes offers substantial benefits, such as improved travel condition predictability and enhanced transportation system reliability. This study presents an in-depth analysis of bus route travel time variability using Global Positioning System (GPS) data, with a specific focus on Nagpur city. The study employs comprehensive citywide GPS data from the regular bus transit system operating in Nagpur, India, to perform the TTV analysis. A route-level examination was conducted to observe daily and intra-day TTV. Various factors contributing to TTV were meticulously analyzed, including route length, journey speed, peak periods, and day of the week. To quantify the impact of these factors, a TTV model was developed using multiple linear regression technique. The analysis revealed significant variability in travel times, influenced primarily by traffic congestion, signal delays, and passenger boarding and alighting patterns. The developed model demonstrated a high level of accuracy, with an adjusted R2 value of 0.953, indicating an excellent fit. This suggests that the model effectively captures the key factors influencing TTV. The findings provide valuable insights for transportation planners and policymakers, enabling them to enhance bus schedule reliability, optimize route planning, and ultimately improve the commuter experience in urban areas.