Background: To develop and validate a nomogram prediction model for assessing the risk of major adverse cardiovascular and cerebrovascular events (MACCE) in patients with nonvalvular atrial fibrillation (NVAF) and heart failure with preserved ejection fraction (HFpEF) within one year of discharge. Methods: We enrolled 828 patients with NVAF and HFpEF from May 2017 to March 2022 in Zhongda Hospital as the training cohort, and 564 patients with NVAF and HFpEF in Taizhou People’s Hospital between August 2018 and March 2022 as the validation cohort. A total of 35 clinical features, including baseline characteristics, past medical records, and detection index, were used to create a prediction model for MACCE risk. The optimized model was verified in the validation cohort. Calibration plots, the Hosmer-Lemeshow test, and decision curve analyses (DCA) were utilized to assess the accuracy and clinical efficacy of the nomogram. Results: MACCE occurred in 23.1% of all patients within one year of discharge. The nomogram identified several independent risk factors for MACCE, including atrial fibrillation duration \ge6 years, poor medication compliance, serum creatinine level, hyperthyroidism, serum N-terminal pro-brain natriuretic peptide level, and circumferential end-diastolic stress. The DCA demonstrated the excellent efficacy of the prediction model for the MACCE end-point, with a wide range of high-risk threshold probabilities in both cohorts. The Hosmer-Lemeshow test confirmed that momogram predictions fit for both the training (p = 0.573) and validation (p = 0.628) cohorts. Conclusions: This nomogram prediction model may offer a quantitative tool for estimating the risk of MACCE in patients with NVAF and HFpEF within one year of discharge.