The optimal approach to classifying multimorbidity burden in assessing treatment-associated outcomes using real-world data remains uncertain. We assessed whether 2 measurement approaches to characterize multimorbidity influenced observed associations of β-blocker use with outcomes in adults with heart failure (HF). We conducted a retrospective study on adults with HF from 4 integrated health care delivery systems. Multimorbidity burden was characterized by either (1) simple counts of chronic conditions or (2) a weighted multiple chronic conditions score using data from electronic health records. We assessed the impact of these 2 approaches to characterizing multimorbidity on associations between exposure to β-blockers and subsequent all-cause death, hospitalization for HF, and hospitalization for any cause. The study population characterized by a count of chronic conditions included 9988 adults with HF who had a mean (SD) age of 76.4 (12.5) years, with 48.7% women and 24.7% racial/ethnic minorities. The cohort characterized by weighted multiple chronic conditions included 10,082 adults with HF who had a mean (SD) age of 76.4 (12.4) years, 48.9% women, and 25.5% racial/ethnic minorities. The multivariable associations of risks of death or hospitalizations for HF or for any cause associated with incident β-blocker use were similar regardless of how multimorbidity burden was characterized. Simple counts of chronic conditions performed similarly to a weighted multimorbidity score in predicting outcomes using real-world data to examine clinical outcomes associated with β-blocker therapy in HF. Our findings challenge conventional wisdom that more complex measures of multimorbidity are always necessary to characterize patients in observational studies examining therapy-associated outcomes.