Objective The purpose of the current research was to analyze the relevant risk factors for short-term death in patients with chronic obstructive pulmonary disease (COPD) and heart failure (HF), and to build a predictive nomogram. Methods We conducted a retrospective analysis of clinical data from 1 323 COPD and HF comorbidity patients who were admitted to the Affiliated Hospital of Southwest Medical University from January 2018 to January 2022. Samples were divided into survival and death groups based on whether they died during the follow-up. General data and tested index of both groups were analyzed, and the discrepant index was analyzed by single factor and multiple factor Logistic regression analysis. R software was applied to create the nomogram by visualizing the results of the regression analysis. The accuracy of the results was verified by C index, calibration curve, and ROC curve. Results The results from the multiple factor Logistic regression analysis indicated that age (OR=1.085, 95%CI 1.048 to 1.125), duration of smoking (OR=1.247, 95%CI 1.114 to 1.400), duration of COPD (OR=1.078, 95%CI 1.042 to 1.116), comorbidity with respiratory failure (OR=5.564, 95%CI 3.372 to 9.329), level of NT-proBNP (OR=1.000, 95%CI 1.000 to 1.000), level of PCT (OR=1.153, 95%CI 1.083 to 1.237), and level of D-dimer (OR=1.205, 95%CI 1.099 to 1.336) were risk factors for short-term death of COPD and HF comorbidity patients. The level of ALB (OR=0.892, 95%CI 0.843 to 0.942) was a protective factor that was used to build the predictive nomogram with the C index of 0.874, the square under the working characteristics curve of the samples of 0.874, the specify of 82.5%, and the sensitivity of 75.0%. The calibration curve indicated good predictive ability of the model. Conclusion The nomogram diagram built by the current research indicated good predictability of short-term death in COPD and HF comorbidity patients.