Disruption prediction and avoidance is a critical need for next-step tokamaks such as ITER. The Disruption Event Characterization and Forecasting Code (DECAF) is used to fully automate analysis of tokamak data to determine chains of events that lead to disruptions and to forecast their evolution allowing sufficient time for mitigation or full avoidance. Disruption event chains related to local rotating or global MHD modes and vertical instability are examined with warnings issued for many off-normal events including density limits, plasma dynamics, confinement transitions, and profile variations. Along with Greenwald density limit evaluation, a local radiative island power balance theory is evaluated and compared to the observation of island growth. Automated decomposition and analysis of rotating tearing modes produce physical event chains leading to disruptions. A total MHD state warning model comprised of 15 separate criteria produces a disruption forecast about 180 ms before a standard locked mode detector warning. Single DECAF event analyses have begun on KSTAR, MAST, and NSTX/-U databases with thousands of shot seconds of device operation using from 0.5 - 1 million tested sample times per device.