This study aims to investigate the public’s preferences for and quantitatively measure the economic value of a pollen forecast system, a new meteorological information service, in South Korea. To directly measure the economic value of the pollen forecast system and its attributes in terms of the public’s preferences, this study used conjoint analysis and a discrete choice model. In the conjoint survey, seven factors were considered as attributes of the pollen forecast system: the forecast area, forecast interval, information type, forecast period, delivery media, forecast accuracy, and price. Based on survey data from the six largest metropolitan areas in South Korea, the authors estimated people’s utility function by a rank-ordered logit model and calculated the relative importance (RI) and marginal willingness to pay (MWTP) for each attribute. People considered price, meaning the additional tax burden, to be the most important attribute, with a relative importance of 42.3%. In descending order of relative importance, price was followed by forecast accuracy, forecast interval, forecast area, forecast period, and information type; these attributes had MWTP values of 0.133, −0.017, 0.098, 0.059, and 0.011 USD month−1, respectively. The results of this study can serve as guidance of government investments in the pollen forecast system and provide an empirical basis for the application of conjoint analysis to economic valuation studies on a wider range of meteorological information services.