Quality of Service(QoS) is the collective effect of service performances and has a direct impact on customer satisfaction. Although QoS is subjective, network performance parameters contributing to QoS can be measured physically. Therefore overall customer satisfaction for each test condition of the performance parameters is evaluated by asking respondents to indicate his or her opinion on a five-category rating scale : excellent, good, fair, poor, and unsatisfactory. The results of these opinion tests can then be used to measure and analyze QoS from the customers' viewpoints. In the previous researches, MOS method quantifies surveyed opinions of respondents by a single value. The opinions are quantified by scaled scores(called opinion scores) from score 1 to 5, and MOS is calculated as an arithmetic mean of the opinion scores. The Cumulative Probability Curve method employs graphical and analytical models of opinion, and may be considered as an improvement over the MOS method in that it is concerned with the distribution of opinion scores rather than a sample mean. However, both of them belong to the class of scoring methods which are subjective in nature. In this paper, we develop a new method for evaluating customer satisfaction without assigning subjective scores to customers' opinion. That is, we estimate the relationship between customer satisfaction and network performance parameters by logit models, which can be used to provide guidelines for network planning. In addition, the proposed approach is compared to Cumulative Probability Curve method in terms of prediction errors, and the results indicate that the former is at least as good as the latter.