The general objective of this study was to assess the influence of risk management on project performance in Rwanda. The study was guided by Specific Objectives such as to evaluate the effect of Risk Identification on Hinga Wunguke project performance in Gatsibo District, To determine the effect of Risk Assessment on Hinga Wunguke project performance in Gatsibo District, To establish the effect of Risk treatment on Hinga Wunguke project performance in Gatsibo District. This study will be conducted in Gatsibo District in the Eastern Province. The time of this research was limited in the period between 2020-2022.This time was enough to generate the desired information. This study adopted a inferential study design. The study involved collection of data at a single point in time in the target population. The total population of this research was 140 employees and managers of Hinga Wunguke Project in Gatsibo district. The sources of data were primary and secondary data. To get primary data, the researcher went to the field and collected raw data from respondents, in this study, questionnaires, interviews and observations were used to collect primary data. Secondary data was collected by way of document reviews. The sample size was 140. To get primary data, the researcher went to the field and collected raw data from respondents, in this study, questionnaires, interviews and observations were used to collect primary data. SPPSS was used to run data after collection. The coefficient of determination R2 =0.744 indicates that approximately 74.4% of the variability in project performance can be explained by the predictors included in the model. Notably, the coefficient for Risk identification (B=0.590,p=0.023) demonstrates a statistically significant positive relationship with project performance. This suggests that for each unit increase in Risk identification, there is a corresponding increase of 0.590 in project performance, with the associated p-value indicating that this relationship is unlikely to have occurred by chance. However, the coefficients for Risk assessment (B=0.017,p=0.886) and Risk treatment (B=0.007,p=0.927) are not statistically significant, indicating that their impact on project performance may be negligible. These high p-values suggest that there is insufficient evidence to reject the null hypothesis, implying that the relationships between Risk assessment, Risk treatment, and project performance are not statistically significant. Consequently, despite having small coefficients, the lack of statistical significance implies that the observed effects of Risk assessment and Risk treatment on project performance may not be reliable or meaningful in the context of the study.
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