This study investigates the drivers of traditional (transport, travel, and government services), modern (financial and insurance, and communication), and composite (total, traditional, and modern) service exports in Kenya. Eight autoregressive and distributed lag (ARDL) models, for each above-mentioned service, are estimated using time series data ranging from 1975 to 2017. Results reveal that total service exports are determined by world demand, goods exports, Real Exchange Rate, human capital, institutions, financial development, and infrastructure. The authors make five major insights at the disaggregated level. First, exports of goods improve exports of all services in the long-run. Second, world demand, which signals external shocks, has a positive effect on traditional services. As for modern services, the effect is positive in the short-run but not in the long-run. Third, the J-curve effect is evident in travel, transport, insurance and financial, and communication services. Fourth, institutions are a short-run phenomenon. Fifth, human capital, financial development, and infrastructure improve most services in the long-run but the effect is negative in the short-run. For purposes of policy, we recommend the promotion of merchandise exports as it improves exports of all services. Other policy instruments vary across services. Therefore, policies should be formulated per service.