Objective: The Health Attitude Survey (HAS) is an 8-item screener designed to assess for somatization in general medical clinics. Similarly, the Health History Checklist (HHC) is a brief checklist of physical symptoms that maps on to DSM-III diagnostic criteria for Somatization disorder. The purpose of this study was to calculate the diagnostic classification statistics for the HAS and HHC both alone and in combination to differentiate between patients with epilepsy and patients experiencing psychogenic non-epileptic events (PNEE). In addition, these findings were then statistically combined using previously published cutoff scores (Benge et al., 2012) from the same sample using the Structured Inventory of Malingered Symptomatology (SIMS). Method: The HAS and HHC were administered to veterans referred as part of a larger neuropsychological screening. All of the patients were referred by the neurology department at a large VA hospital and were undergoing week-long observation on an epilepsy monitoring unit. Group membership (epilepsy vs PNEE) was determined by a board-certified neurologist and director of the epilepsy program. 180 of the patients were successfully classified as either having epilepsy (n = 82) or PNEE (n = 98) using “gold standard” video EEG findings following induction. Results: Using a cut-score > 19, the HAS demonstrated good diagnostic classification statistics in patients diagnosed using vEEG (SE = .54, SP = .92; 68% post-test probability). Using a cut-score > 16, the HHC was relatively poor at identifying PNEE (SE = .24, SP = .90; 45% post- test probability). However, chaining the likelihood ratios of the two measures resulted in a post-test probability of 84% when a positive finding occurred on both measures. Finally, chaining the likelihood ratios from this study with the published SIMS cutscore > 22 (SE = .39, SP = .90) recommended for this same population resulted in a post-test probability of 95%. Conclusion: None of the included self-report inventories were particularly impressive at identifying PNEE on their own; however, combining the measures resulted in considerable more accuracy in identifying PNEE. These brief measures represent a cost-effective way of screening individuals for PNEE and might be effective for identifying other somatoform disorders. Limitations include not all patients being induced and a few patients with both PNEE and confirmed epilepsy.