Background The first COVID-19 case in Kenya was confirmed on March 13th, 2020. Here, we provide forecasts for the potential incidence rate, and magnitude, of a COVID-19 epidemic in Kenya based on the observed growth rate and age TRANS distribution of confirmed COVID-19 cases observed in China, whilst accounting for the demographic and geographic dissimilarities between China and Kenya. Methods We developed a modelling framework to simulate SARS-CoV-2 transmission TRANS in Kenya, KenyaCoV. KenyaCoV was used to simulate SARS-CoV-2 transmission TRANS both within, and between, different Kenyan regions and age groups TRANS. KenyaCoV was parameterized using a combination of human mobility data between the defined regions, the recent 2019 Kenyan census, and estimates of age group TRANS social interaction HP social interaction TRANS rates specific to Kenya. Key epidemiological characteristics such as the basic reproductive number TRANS and the age TRANS-specific rate of developing COVID-19 symptoms after infection MESHD with SARS-CoV-2, were adapted for the Kenyan setting from a combination of published estimates and analysis of the age TRANS distribution of cases observed in the Chinese outbreak. Results We find that if person-to-person transmission TRANS becomes established within Kenya, identifying the role of subclinical, and therefore largely undetected, infected individuals is critical to predicting and containing a very significant epidemic. Depending on the transmission TRANS scenario our reproductive number TRANS estimates for Kenya range from 1.78 (95% CI 1.44 - 2.14) to 3.46 (95% CI 2.81-4.17). In scenarios where asymptomatic TRANS infected individuals are transmitting significantly, we expect a rapidly growing epidemic which cannot be contained only by case isolation. In these scenarios, there is potential for a very high percentage of the population becoming infected (median estimates: >80% over six months), and a significant epidemic of symptomatic COVID-19 cases. Exceptional social distancing measures can slow transmission TRANS, flattening the epidemic curve, but the risk of epidemic rebound after lifting restrictions is predicted to be high.