Purpose: Oncologists for pancreatobiliary cancer (PBca) demand a new circulating biomarker superior to carbohydrate antigen 19-9 (CA19-9). This study aimed to identify the serum microRNA signature composed of reproducible and disease-related microRNAs with clinical bioinformatics. Methods: This multicenter study enrolled patients with treatment-naïve PBca and healthy participants. Optimized serum processing condition was evaluated with t-distributed stochastic neighbor embedding (t-SNE) visualization. The serum microRNA candidates were selected in disease association with Weighted Gene Coexpression Network Analysis (WGCNA). A microRNA signature, combination of multiple serum microRNAs, was examined in exploratory, validation and independent validation set. Biology of the diagnostic miRNAs was evaluated using human pancreatic cancer cells. Results: The 284 (healthy 150, PBca 134) of 827 serum samples were processed within 2hr of time-to serum collection, distributed at the same area of t-SNE map, assigned to exploratory set. The 193 optimized samples were assigned to validation (healthy 50, PBca 47) or independent validation set (healthy 50, PBca 46). Index-1 was a combination of the 5 serum microRNAs having disease-association on WGCNA, showed a sensitivity/specificity >80% and an AUC outperforming CA19-9 in exploratory, validation and independent validation set. The AUC of Index-1 for detecting T1 tumor was superior to CA19-9 (0.856 vs. 0.649, p = 0.038). Human pancreatic cancer cells had intra- and extracellular expression of miR-665, a component of Index-1. Transfection of miR-665 to a human pancreatic cancer cell inhibited cell growth. Conclusions: A serum microRNA signature, Index-1, was useful for detecting PBca, which would improve the early diagnosis of PBca. Overall design: 284 (healthy 150, PBca 134) serums were analyzed in the training set, and 93 serums were assigned to validation (healthy 50, PBca 47) or independent validation set (healthy 50, PBca 46). Tripricate analyses per a sample.