Therapeutic development for type 1 diabetes (T1D) continues to face challenges in endpoint and cohort selection. While it is known that individuals who develop islet cell autoantibodies (AAbs) are at higher risk for developing T1D, it remains unclear what other factors may lead to increased risk for T1D. The aim of this project was to inform T1D prevention clinical trial designs by developing a quantitative joint model based-clinical trial simulation (CTS) tool. Individual-level data from the NIH TEDDY and TrialNet TN01 natural history studies were used. The studies followed AAb+ individuals at risk of developing T1D. To describe T1D disease progression quantitatively, longitudinal and time-to-event variables were simultaneously modelled with the 2-hour oral glucose tolerance test (OGTT) measure at the event time, included as a time-varying covariate. Baseline covariates identified to increase the probability of the T1D diagnosis were the presence of the IA2A AAb, a high HbA1c value, a high fasting OGTT value, and a high fasting OGTT to 2-hour OGTT ratio. Covariates decreasing the risk were a high BMI and the presence of GADA AAb. The developed model based-CTS tool, where users can specify the trial design, participants characteristics and hypothetical drug effect, provides a framework to perform T1D prevention clinical trial simulations with the intention to assist the trial design decision-making process.