With the continuous development of IC industry and the continuous pursuit of high energy efficiency, the process size is constantly shrinking. More and more circuits work in the sub-threshold domain, and the fluctuation of process parameters leads to the non-Gaussian distribution of circuit delay. Statistical static timing analysis is a new method to analyze the timing in advanced process, which can accelerate timing convergence and display the expected yield by adopting a method of expressing process parameters and delay with random variables. This paper mainly studied the statistic modeling method of circuit cell delay fluctuation in sub-threshold domain. The models of Monte Carlo gold standard data for single timing arc and multiple timing arcs were built up respectively. A distributed fitting statistical modeling method for single timing arc cell delay is proposed, and the error is less than 6.30%. An artificial neural network statistical modeling method for multiple timing arcs cell delay is proposed, and the error is less than 4.95%.