Paired comparison is popular in preference trials. The estimated Scores have high accuracy, even if the data include measurement errors. However, incomplete comparison becomes inevitable, especially when the number of objects to be scored is large. In such cases, high precision by paired comparison is not guaranteed. In this paper, we propose a maximum likelihood estimation of scores, based on four-fold choice data. An empirical study of flower preference showed that the method of four-fold choice takes about the same time as a paired comparison, and the estimated scores were almost the same for the two procedures. It was clearly shown, by numerical simulation, that the precision of the estimated score of the most preferred object does not decrease with an increased number of objects to be compared in the method of four-fold choice. This is in great contrast to the paired comparison method. The estimated scores of less preferred objects have larger variances in the method of four-fold choice, whereas those from paired comparisons have similar variances for all objects. Thus, the four-fold choice method is effective when the scores of Most preferred objects are matters of concern.