A reliable livestock disease surveillance system should detect changes in health events whenever they occur. Such a system ought to be evaluated regularly to ensure it provides valuable information in an efficient manner. Thus, a cross-sectional study was carried out in 2017 to assess eight attributes of the livestock disease surveillance systems in Pallisa and Kumi districts, Uganda. A total of 772 livestock farmers were interviewed to evaluate the surveillance system at their level, using a structured questionnaire. Guided interviews were also carried out with 13 key informants who included all veterinary staff at the districts and sub-county administrative units, as well as two officials at the Ministry of Agriculture Animal Industry and Fisheries (MAAIF). The stakeholders interviewed at the three different levels of the livestock diseases surveillance system perceived the system as useful, with ability to detect epidemics and initiate their control if they occurred. The surveillance system was perceived to be considerably representative, sensitive and acceptable, with the ability to generate data of good quality. However, key emerging issues that need improvement were noted. These included poor laboratory diagnostic services, inability to work within the means of available resources, slow data transmission and feedback, and nonspecific surveillance forms leading to poor quality of data collected. Poor communication along the surveillance system chain and inadequate staffing were noted as the major challenges faced by the surveillance system in the two districts. Although perceived to be functional, the livestock surveillance requires improvements for efficient disease detection and control. For better performance, the surveillance system could be strengthened by establishing and equipping laboratories for efficient confirmatory diagnosis of diseases; adjusting to work within the means of available resources; improving the reporting process through quick data transmission and quick feedback and designing precise surveillance form to improve quality of data collected.