Necroptosis, pro-inflammatory programmed necrosis, has been reported to exert momentous roles in pancreatic cancer (PC). Herein, the objective of this study is to construct a necroptosis-related prognostic model for detecting pancreatic cancer. In this study, the intersection between necroptosis-related genes and differentially expressed genes (DEGs) of pancreatic ductal adenocarcinoma (PDAC) was obtained based on GeneCards database, GEO database (GSE28735 and GSE15471), and verified using The Cancer Genome Atlas (TCGA). Next, a prognostic model with Cox and LASSO regression analysis, and divided the patients into high-risk and low-risk groups. Subsequently, the Kaplan–Meier (KM) survival curve and the receiver operating characteristic (ROC) curves were generated to assess the predictive ability of overall survival (OS) of PC patients. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed to predict the potential biofunction and possible mechanical pathways. The EMTome database and an immune analysis were applied to further explore underlying mechanism. Finally, clinical samples of PDAC patients were utilized to verify the expression of model genes via immunohistochemistry (IHC), and the normal human pancreatic ductal cell line, hTERT-HPNE as well as human pancreatic ductal carcinoma cell lines, PANC-1 and PL45, were used to identify the levels of model genes by Western blot (WB) and immunofluorescence (IF) in vitro. The results showed that 13 necroptosis-related DEGs (NRDEGs) were screened based on GEO database, and finally four of five prognostic genes, including KRT7, KRT19, IGF2BP3, CXCL5, were further identified by TCGA to successfully construct a prognostic model. Univariate and multivariate Cox analysis ultimately confirmed that this prognostic model has independent prognostic significance, KM curve suggested that the OS of low-risk group was longer than high-risk group, and the area under receiver (AUC) of ROC for 1, 3, 5 years was 0.733, 0.749 and 0.667, respectively. A GO analysis illustrated that model genes may participate in cell–cell junction, cadherin binding, cell adhesion molecule binding, and neutrophil migration and chemotaxis, while KEGG showed involvement in PI3K-Akt signaling pathway, ECMreceptor interaction, IL-17 signaling pathway, TNF signaling pathway, etc. Moreover, our results showed KRT7 and KRT19 were closely related to EMT markers, and EMTome database manifested that KRT7 and KRT19 are highly expressed in both primary and metastatic pancreatic cancer, declaring that model genes promoted invasion and metastasis potential through EMT. In addition, four model genes were positively correlated with Th2, which has been reported to take part in promoting immune escape, while model genes except CXCL5 were negatively correlated with TFH cells, indicating that model genes may participate in immunity. Additionally, IHC results showed that model genes were higher expressed in PC tissues than that in adjacent tumor tissues, and WB and IF also suggested that model genes were more highly expressed in PANC-1 and PL45 than in hTERT-HPNE. Tracing of a necroptosis-related prognostic model for pancreatic carcinoma reveals its invasion and metastasis potential through EMT and immunity. The construction of this model and the possible mechanism of necroptosis in PDAC was preliminarily explored to provide reliable new biomarkers for the early diagnosis, treatment, and prognosis for pancreatic cancer patients.