Objective  To investigate the risk factors for the occurrence of central venous stenosis (CVS) in patients undergoing maintenance hemodialysis (MHD) and to evaluate their predictive capabilities.  Methods   A retrospective study was conducted on the clinical data of 146 MHD patients treated at the First Affiliated Hospital of Gannan Medical University between January 2022 and September 2023. Seventy-five patients diagnosed with CVS were assigned to the observation group (comprising 54 cases of primary stenosis and 21 cases of restenosis), and 71 patients without CVS symptoms served as the control group. General clinical data and laboratory parameters were collected. Intergroup differences and univariate and multivariate logistic regression were used to identify the independent risk factors. The predictive performance was estimated using the area under the receiver operating characteristic curve (AUC) and other relevant indices.  Results  Intergroup analysis showed that the observation group had lower lymphocyte count (Z=-3.350, P＜0.001) and higher neutrophil-to-lymphocyte ratio (NLR) (Z=2.878, P=0.004) and platelet volume related indices (PVIs) (Z=3.500, P＜0.001), as compared those with the control group. Compared with the primary stenosis group, the restenosis group had bigger mean platelet volume (MPV) (t=-2.152, P=0.037), which was an independent risk factor for restenosis following CVS intervention (OR=1.821, 95% CI: 01.020～3.247, P=0.043). Multifactorial logistic regression indicated that lymphocyte count (OR=0.102, 95% CI: 0.016～0.653, P=0.016) and PVIs (OR=1.343, 95% CI: 1.015～1.778, P=0.039) were the independent risk factors for CVS in MHD patients. The predictive performance of PVIs (AUC=0.849) was superior to that of the lymphocyte count (AUC=0.798). The predictive value for CVS by combined both factors yielded an AUC of 0.854, with a sensitivity of 80.8% and a specificity of 78.4%.  Conclusion  PVIs and lymphocyte count are independent risk factors for the development of CVS in MHD patients. Combination of these two parameters obtains a higher predictive value and can serve as effective biomarkers for early screening and risk assessment of CVS.