Background: Alternative splicing (AS) modifies 92-94% human genes, abnormal splicing events might relate to tumor development and invasion. Glioblastoma Multiforme (GBM) is a fatal, invasive, and malignant tumor in nervous system. The recurrence and development leads to poor prognosis. However, few studies have focused on AS in GBM. Methods: RNA-seq and Alternative splicing events (ASEs) data of GBM samples were downloaded from The Cancer Genome Atlas (TCGA) and TCGASpliceSeq databases, respectively. Firstly, the Cox regression analysis was utilized to identify the overall survival splicing events (OS-SEs). Secondly, a multivariable model was applied to access the prognostic value of risk score. Then, we constructed a co-expressed network between splicing factors (SFs) and overall survival alternative splicing events (OS-SEs). Additionally, to explore the relationship between the potential prognostic signaling pathways and OS-SEs, we constructed a network between these pathways and OS-SEs. Ultimately, to better explain the results, validations from multi-dimension platforms were applied. Results: In the first step, 1,062 OS-SEs were selected by Cox regression. Then, 11 OS-SEs were integrated in a multivariate model by Lasso regression. The area under the curve (AUC) of receiver operator characteristic (ROC) curve was 0.861. In addition, the risk score generated from the multivariate model was confirmed to be an independent prognostic factor (P < 0.001). What's more, in the network of SFs and ASEs, CELF5 significantly regulated GSG1L|35696|AP and GSG1L|35698|AP (P < 0.001, R = 0.511 and =-0.492). Additionally, GSG1L|35696|AP (P = 0.006) and GSG1L|35698|AP (P = 0.007) showed a significant relationship with cancer status. Eventually, KEGG pathways related to