The ability to make termination decision is an important index that influences on the venture capital firms’ long term performance. However, present termination decision methods ignore the information release effect during the emerging technology firm development process. Aiming at this problem, the information release during the emerging technology firm development process is induced and analyzed firstly; then the good (bad) signal observed by venture capitalist is chosen as the binary learning signal, three conditions that the good (bad) signal observed along with the emerging technology firm development are considered, from the view of Bayesian posterior estimate, a signal learning model is proposed; the exogenous optimal stopping point is decided according to venture capitalist’s psychological threshold which reflects venture capitalist’s altitude to risk farther more; and an example is given at the end. The model is a dynamic one based on the Bayesian posterior estimate; and it reflects the information dynamic development influences on the following decision. The model provides a theoretical reference for venture capitalist’s termination decision in time, and it also gives a reasonable explanation for the enterpriser’s “window dressing” behavior.