This paper discusses the use of conjoint analysis to elicit preferences for healthcare services. Conjoint analysis is a rigorous survey method that helps policymakers understand how patients and the community value different aspects of healthcare. The technique has been successfully applied in various areas, including market research, transport economics, and environmental economics. In healthcare, it can be used to estimate the relative importance of different service characteristics, show trade-offs between these characteristics, and rank healthcare services based on patient preferences. The paper outlines the five stages of conducting a conjoint analysis study: identifying characteristics, assigning levels to these characteristics, choosing scenarios, establishing preferences through ranking, rating, or discrete choices, and analyzing data using regression techniques. An example application in orthodontic care is provided, where the trade-offs between location and waiting time were evaluated. The results showed that respondents preferred local clinics over hospital clinics and were willing to wait longer for appointments at local clinics. The paper also highlights methodological issues, such as defining characteristic levels, handling inconsistent responders, and modeling the benefit function. Despite these challenges, conjoint analysis has great potential in healthcare decision-making and should be further explored and applied with caution.This paper discusses the use of conjoint analysis to elicit preferences for healthcare services. Conjoint analysis is a rigorous survey method that helps policymakers understand how patients and the community value different aspects of healthcare. The technique has been successfully applied in various areas, including market research, transport economics, and environmental economics. In healthcare, it can be used to estimate the relative importance of different service characteristics, show trade-offs between these characteristics, and rank healthcare services based on patient preferences. The paper outlines the five stages of conducting a conjoint analysis study: identifying characteristics, assigning levels to these characteristics, choosing scenarios, establishing preferences through ranking, rating, or discrete choices, and analyzing data using regression techniques. An example application in orthodontic care is provided, where the trade-offs between location and waiting time were evaluated. The results showed that respondents preferred local clinics over hospital clinics and were willing to wait longer for appointments at local clinics. The paper also highlights methodological issues, such as defining characteristic levels, handling inconsistent responders, and modeling the benefit function. Despite these challenges, conjoint analysis has great potential in healthcare decision-making and should be further explored and applied with caution.