DUV lithography has introduced a progressive mask defect growth problem widely known as crystal growth or haze. Even if the incoming mask quality is good, there is no guarantee that the mask will remain clean during its production usage in the wafer fab. These progressive defects must be caught in advance during production in the fabs. The ideal reticle quality' control goal should be to detect any nascent progressive defects before they become yield limiting. So, a high-resolution mask inspection is absolutely needed, but the big question is: "how often do fabs need to re-inspect their masks"? Previous work towards finding a cost effective mask re-qualification frequency (V. Samek et al., September 8-10, 1999), was done prior to the above mentioned progressive defect problem that industry started to see at a much higher rate during just the last few years. Other related recent work was done 2004 BACUS conference which is dedicated to DRAM fab data (K. Bhattacharyya et al., 2004). In this paper a realistic mask re-qualification frequency model has been developed based on a large volume of data from an advanced logic fab. This work will compliment previous work in this area done with the data from a DRAM fab (K. Bhattacharyya et al., 2004). Statistical methods are used to analyze mask inspection and product data, which are combined in a stochastic model