Dissolved Gas Analysis (DGA) is usually performed for power transformer condition based maintenance (CBM) activities. In reality, the interpretation of DGA data is complex and done through several knowledge sources. Lack of information within these knowledge sources necessitates an information fusion methodology. Constructed upon Dempster-Shafer (DS) theoretic approach, this paper proposes a novel interpretation rule and algorithm. Weibull functions were utilized to quantify the degree of belief in major fault according to respective DGA parameters. Threshold belief mass (THB) that distinguishes incipient fault from major fault, which is located within the interval of degree of belief in major fault were observed. In this paper, based on minimum threshold values, a novel rule termed as Threshold Belief Mass (THB) interpretation rule is proposed and compared with Dempster's and Yager's combination rule. Furthermore, from the result of THB interpretation rule and belief or plausibility function, different level of transformer's condition is suggested. Several operational and maintenance decision-making proposal are introduced for a system operator with respect to the belief and plausibility function. In summary, the new method enables a system operator to interpret DGA data more systematically.