Five years since the adoption of the Sendai Framework for Disaster Risk Reduction 2015-2030, the concept of building resilience amongst communities to flooding is still a major concern in developing countries. This is evident from the ever-increasing flood events across Kenya and the inability of communities affected by floods to act appropriately prior to a flood event. Kwale County, in Kenya, the example of this study typifies this situation. Kenya Red Cross Society implemented a project whose goal was to strengthen institutional and community capacity in anticipatory flood risk management. The project employed the early warning services (EWS) model in understanding knowledge of flood risks. To investigate flood risk in Kwale County, openly available geo-information tools were used in systematic collection of information to understand areas exposed to floods, the communities affected and impacts they experience. These tools included; the Height Above Nearest Drainage (HAND) that identified flood prone areas and dwellings at risk of flooding from satellite imagery analysis. Open Street Map Automated Navigation Directions (OsmAnd) mobile navigation system that geo-located dwellings at risk of flooding and Kobo that collected geo-tagged data to validate inhabited buildings as to whether they are at risk of flooding. The results showed that, HAND technique identified dwellings at risk of flooding with 89% accuracy. Geo-location using OsmAnd showed that most houses identified to be at risk of flooding were falling within a circle with a radius of 5 meters. The results also show that the majority of the study area is characterized by moderate to very high flood hazard risks; 16% characterized by very high flood hazard risk, while 26% are at medium risk of flooding. This study demonstrates that HAND is a reliable tool for identification of houses at risk of flooding. The county government of Kwale and other acting institutions should endeavour in the use of these geo-information tools in investigating flood risk. Information obtained from these tools will enable such institutions to understand flood prone areas and communities at high risk of floods for better prioritization of early warning system needs and in guiding flood preparedness and early response activities.