To improve the software quality, researchers have focused their effort on developing and validating effective methods of finding and fixing defects early in the development process. Software inspections are most widely used defect detection method. Also, researchers showed that the overall effectiveness of an inspection team is affected by the effectiveness of individual inspectors. But researchers have not been able to completely understand the inherent characteristic that makes an individual inspector effective. This paper investigates this problem by analyzing the learning style (LS) preferences of individuals who make up inspection team. Also presents a tool that provides ability to researchers to study the relationship between inspectors’ LS and his/her effectiveness in uncovering defects in software requirement document. Cluster and Discriminant analysis techniques were used to sort inspection teams based on their LS preferences. Researchers can use this tool to study further correlations between inspector’s LS and their performance in team.