To explore the predictive effect of alternative splicing events and splicing factors on the prognosis of kidney renal papillary cell carcinoma patients. Methods  The relevant clinical and transcriptome information of kidney renal papillary cell carcinoma cancer patients were downloaded from TCGA database, and the alternative splicing events information was obtained from TCGASpliceSeq datebase. LASSO and Cox regression models were used to screen the relevant alternative splicing events and splice factors by R language package. The related model was established, and the independent prognostic analysis and related regulatory network analysis were performed. Results  Univariate Cox proportional hazard regression model identified 1 405 alternate splicing events as diseaserelated splicing events, including 98 AA events, 101 AD events, 333 AP events, 346 AT events, 448 ES events, 3 ME events, and 76 RI events. Multivariate Cox regression analysis showed that with clinical related information, alternative splicing events（C16orf13|32924|ES、TSFM|22759|ES、MACF1|1881|ES、 ATP5C1|10726|ES、UNG|24277|AP、UNKL|33077|AP）may be independent prognostic factors for predicting prognosis (HR=1.028，95%CI:1.018～1.039，P<0.01).Conclusions  The combination of alternate splicing events and related clinical data has certain significances in predicting the effectiveness of treatment in kidney renal papillary cell carcinoma patients, and plays an important role in the research on the research of kidney renal papillary cell carcinoma prognosis.