Randomness in Negative Bias Temperature Instability (NBTI) process poses a dramatic challenge on reliability prediction of digital circuits. Accurate statistical aging prediction is essential in order to develop robust guard banding and protection strategies during the design stage. Variations in device level and supply voltage due to Dynamic Voltage Scaling (DVS) need to be considered in aging analysis. The statistical device data collected from 65nm test chip shows that degradation behavior derived from trapping/detrapping mechanism is accurate under statistical variations compared to conventional Reaction Diffusion (RD) theory. The unique features of this work include (1) Aging model development as a function of technology parameters based on trapping/detrapping theory (2) Reliability prediction under device variations and DVS with solid validation with using 65nm statistical silicon data (3) Asymmetric aged timing analysis under NBTI and comprehensive evaluation of our framework in ISCAS89 sequential circuits. Further, we show that RD based NBTI model significantly overestimates the degradation and TD model correctly captures aging variability. These results provide design insights under statistical NBTI aging and enhance the prediction efficiency.