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Background: Patients receiving maintenance hemodialysis frequently require ambulance transport to the emergency department (ambulance-ED transport). Identifying predictors of outcomes after ambulance-ED transport, especially the need for timely dialysis, is important to health care providers., Objective: The purpose of this study was to derive a risk-prediction model for urgent dialysis after ambulance-ED transport., Design: Observational cohort study., Setting and Patients: All ambulance-ED transports among incident and prevalent patients receiving maintenance hemodialysis affiliated with a regional dialysis program (catchment area of approximately 750 000 individuals) from 2014 to 2018., Measurements: Patients' vital signs (systolic blood pressure, oxygen saturation, respiratory rate, and heart rate) at the time of paramedic transport and time since last dialysis were utilized as predictors for the outcome of interest. The primary outcome was urgent dialysis (defined as dialysis in a monitored setting within 24 hours of ED arrival or dialysis within 24 hours with the first ED patient blood potassium level >6.5 mmol/L) for an unscheduled indication. Secondary outcomes included, hospitalization, hospital length of stay, and in-hospital mortality., Methods: A logistic regression model to predict outcomes of urgent dialysis. Discrimination and calibration were assessed using the C-statistic and Hosmer-Lemeshow test., Results: Among 878 ED visits, 63 (7.2%) required urgent dialysis. Hypoxemia (odds ratio [OR]: 4.04, 95% confidence interval [CI]: 1.75-9.33) and time from last dialysis of 24 to 48 hours (OR: 3.43, 95% CI: 1.05-11.9) and >48 hours (OR: 9.22, 95% CI: 3.37-25.23) were strongly associated with urgent dialysis. A risk-prediction model incorporating patients' vital signs and time from last dialysis had good discrimination (C-statistic 0.8217) and calibration (Hosmer-Lemeshow goodness of fit P value .8899). Urgent dialysis patients were more likely to be hospitalized (63% vs 34%), but there were no differences in inpatient mortality or length of stay., Limitations: Missing data, requires external validation., Conclusion: We derived a risk-prediction model for urgent dialysis that may better guide appropriate transport and care for patients requiring ambulance-ED transport., Competing Interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article., (© The Author(s) 2023.)