|Geo-information technology has been integrated with various sectors of development to help achieve sustainability and improve the delivery of services and smooth operation of activities within the economy. However, considering the technology was not given much importance in the previous decades, integrating it has been a slow process as people are still stuck in the traditional way of doing things. The world is generally changing daily with new technologies being introduced and new problems arising due to the growing population and an increase in demand for services and goods. The issue of traffic congestion is among these problems and solving it will involve integrating various measures, and GIS is what this study intends to propose to support this move. Third-world economies are experiencing rapid urbanization and this is exerting pressure on the existing infrastructure and resources due to the high population growth. The high rate of urbanization has created more employment opportunities in these urban areas and this has attracted many people to the cities. One such effect is being experienced by Nairobi city, Kenya’s capital. In as much as the growth of the city has trickled down benefits to the neighboring areas, the city experiences problems of traffic congestion which has led to a deterioration in its aesthetic value, pollution, and a delay in the delivery of services. Nairobi Central Business District is a key administrative center, business center, and commercial center, among others contributing to a myriad of its woes among them being congestion. Being a core economic center for the county and the country in general, there is a major need to come up with effective strategies to decongest the city’s CBD. Considering that several strategies have been tried before without much impact, the strategy therefore ought to be sustainable. This study therefore aimed at incorporating GIS in developing strategies that support traffic decongestion of the study area. Both spatial and non-spatial data was collected and GIS was the main method of data collection, as well as data analysis. The geographical location of friction points along the identified streets were picked and visualized on a map, and these constituted of on-street parking, street vending, and undesignated bus drop-offs. These were identified to be the key causes of traffic congestion along major streets such as Moi Avenue, and Kenyatta Avenue. Since the study was only limited to Nairobi’s CBD, it further recommends for same to be extended to the larger Nairobi metropolitan, as it also contributes to the traffic congestion within the CBD.