Abstract Background Niemann-Pick disease Type C (NP-C) is a lysosomal lipid storage disorder with varying symptomatology depending on the age of onset. The diagnosis of NP-C is challenging due to heterogeneous nonspecific clinical presentation of the disease. NP-C Suspicion Index (SI) was developed to aid screening and identification of patients with suspicion of NP-C for further clinical evaluation. Here we assess the performance of five NP-C SI models to identify patients with NP-C compared with clinical practice to determine the best SI model for identification of each clinical form of NP-C by age. Methods This was a post hoc analysis of a retrospective chart review of patient data collected from five expert NP-C centers. The study assessed the proportion of patients with NP-C who could have been identified using the Original SI, Refined SI, 2/7 SI, 2/3 SI, and Early-Onset SI and evaluated the performance of each SI against clinical practice. A score above a threshold of 70 points for the Original SI, 40 points for the Refined SI, 6 points for the Early-Onset SI, and 2 points for the 2/7 and 2/3 SIs represented identification of NP-C. Results The study included 63 patients, and of these, 23.8% had a family history of NP-C. Of the available SI tools, the Refined SI performed well in identifying patients with NP-C across all age groups (77.8% infantile, 100% juvenile and 100% adult groups), and earlier identification than clinical diagnosis would have been possible in 50.0% of infantile, 72.7% of juvenile and 87.0% of adult patients. Patients who were not detected by the Refined SI prior to clinical diagnosis mainly presented with delayed developmental milestones, visceral manifestations, neurologic hypotonia, clumsiness, ataxia, vertical supranuclear gaze palsy, parent or siblings with NP-C, dysarthria/dysphagia and psychotic symptoms. Conclusion This study demonstrated the applicability of various SI models for screening and identification of patients with NP-C for further clinical evaluation. Although NP-C is rare and the patient population is limited, this study was conducted in a real-world setting and confirms SI models as useful screening tools that facilitate identification of patients with NP-C earlier in their disease course.