Objectives: There is a growing demand for mobile monitoring app for peritoneal dialysis (PD) patients, due to factors including the pandemic and increasing percentage of at-home care for dialysis patients in Korea. However, the problem of choosing which key attributes to be provided by the App, in order to meet the demands of patients and physicians, has not been fully explored. This study aims to investigate the preferences of PD patients and physicians on major features of mobile monitoring apps and suggest a promising direction for the development of such apps. Methods: A total of 130 PD patients (mean age 45.1 years [SD 9.4]) and 32 healthcare professionals (87.5% physicians) completed the survey during March to May 2022. A choice-based conjoint (CBC) analysis was conducted using 5 attributes and 3 levels for each attribute. The final profile sets were randomly generated in Conjointly (Sydney, Australia) platform. We calculated the estimates of relative importance (RI) for each attribute and level with willingness-to-pay (WTP). Results: Other than Price, the two most preferred attributes differed. While Emergency consultation (whenever needed) (23.0%) and Consultation on a regular basis (22.2%) were relatively important in the PD patient group, healthcare professionals preferred Data management (22.4%) and Emergency consultation (whenever needed) (21.4%). For Emergency consultation (whenever needed) attribute, both PD patients and healthcare professional groups preferred ‘Consultation by nurse’ (14.5% and 11.4%, respectively) to ‘C24-hour chatbot' (2.1% and -2.3%, respectively). Healthcare professionals’ WTP for Data management increased by KRW 2,789 if ‘Monitoring patient’s daily health records’ were added. Conclusions: Further development of Mobile monitoring apps for PD patients is recommended to maintain features for consultation by human resources, rather than completely automating the process by chatbot, and focus more on providing efficient tools for managing and visualizing daily recorded personal clinical data.