This study examined the impact of COVID-19 pandemic on the performance of the floriculture sector in Kenya with a specific reference and focus on Karen Roses from the year 2016 to 2021.The floriculture industry is one of the largest sectors that helps in the contribution of the Kenyan GDP. Kenya has been the leading exporter to Europe with about 25 percent on the market share. COVID-19 has had a particularly negative impact on Kenya's cut-flower industry, which have long been a vital supplier for shops, weddings, and funerals in Europe and abroad. The company lost a crucial portion of its logistical supply chain due to restrictions on international flights and domestic transportation. Weddings, funerals, and other public gatherings all came to a halt and were severely reduced around the world, and demand for the commodity peaked. As a result, several flower growers, including Karen Roses, were compelled to throw away unsold blossoms. The study specifically focused on the following objectives: to investigate how the COVID-19 affected the production of the flowers, to determine the effects of Health Protocols on the Performance of Floriculture and to find out the policies and programs they implemented to cope up with COVID-19 pandemic. The study’s target population was 220 flower farms in Kenya with Karen Roses being the study population. The primary data was collected using questionnaires both open and closed methods and secondary data analyzed with Microsoft Excel and presented using descriptive statistics such as the pie charts and graphs. In order to understand how to recover from the COVID-19 pandemic and be ready to handle in the event of a future pandemic, this research project will also benefit the management sector of other flower farms, which will use it to make policy decisions. The key findings of this study were as follows; on the first research question which was to determine the effect of COVID-19 on the production of flowers, we found out that the descriptive statistics showed that production was affected by COVID-19, however, the inferential statistic implied the opposite that production was not affected by COVID-19, on the second research question which was to determine how the health protocols affected the performance of floriculture sector, we found out that both the descriptive statistics and inferential statistic showed that health protocols affected the performance of floriculture sector, hence we achieved our objective, on the third research question which was to find out if the measures that they implemented helped them cope up with COVID-19 pandemic, we found out that both the descriptive statistics and inferential statistic showed that the measures implemented affected the performance of floriculture sector, hence we achieved our objective. The study recommends the following policies which will help in case of any pandemic in the future; subsidy policy, monetary policy, fiscal policy and non-restrictions for the cargo freights policy. Other recommendations for further research were to use the logistic linear model because the data is categorical, in the event that new ideas are developed as a result of our work, we advise that existing hypotheses be reviewed and expanded during subsequent research and based on a case study that includes the majority of Kenya's flower farms, we advise conducting more research on the overall impact of COVID-19 on the performance of the floriculture sector.