ABDUSHAKUR KHATIB LENDAPANA2026-06-022024-10https://repository.mua.ac.ke/handle/123456789/2235Despite all the disaster risk management measures that are in place, disasters have continued to rock Baringo County. This research aimed at assessing effect of disaster risk management systems on disaster risk resilience of Kenyan counties, using Baringo County as case. Specifically, the study aimed at; to determine the effects of disaster risk awareness on disaster risk resilience in Baringo County, to examine the effects of disaster risk governance on disaster risk resilience in Baringo County, to assess the effects of risk reduction measures on disaster risk resilience in Baringo County and to examine the effect of disaster preparedness measures on disaster risk resilience in Baringo County. System Theory, Institutional Theory and Stakeholder Theory was used as the theoretical framework underpinning the study and employed a cross-sectional case study method. A total of 405 officers were targeted who work in sectors with responsibility in disaster risk management within Baringo County comprising of Directorate of DRM, department of Agriculture and Livestock, Water, Health and Nutrition, Fire, Security and peace building and NGOs/Development partners implementing Disaster Risk Reduction initiatives at the county level. A stratified random sampling was used to get the research subjects. Data collection was done using structured questionnaire. The quantitative data collected was analyzed quantitatively by use of descriptive and inferential statistics with the aid of SPSS software version 27. A multiple regression model was applied to demonstrate the association between the independent variables and the dependent variable of disaster risk resilience, and the results was presented in tables, charts and bars. Overall, the study findings showed that there exists a strong positive relation between the independent and the dependent variables as shown by R = 0.799 and R2 = 0.638 this means that 64% of variation in disaster risk resilience is explained by changes in all the independent variables. The level of significance was <0.000 thus the overall regression model significantly predicted the dependent variables. the findings also showed that disaster preparedness measures were the predictor that most effects disaster risk resilience in Baringo County with Unstandardized coefficient (β) value of .479 followed by disaster risk reduction measure with β of .205. Disaster risk awareness was the least significant determinant of disaster risk resilience in Baringo County with Unstandardized coefficient β of .047. This study recommends that Baringo County government and its partners need to continue strengthening investment in all four independent variables as evident has shown they play complimentary role in addressing disaster risk resilience.Thesis