In microblog networks, the propagation of messages is closely related to the influence of opinion leaders. However, it is hard to quantitate the influence of opinion leaders in different types of messages, which bring great challenges to evaluate the influence of opinion leaders and predict the propagation trend of a message. To solve this problem, this paper proposes a method to measure and analyze opinion leaders' influence in microblog based on the dynamical process of message propagation. By studying the spread patterns of messages, dynamical directed graph is employed to model the propagation process. The propagation of a message can be decomposed into sub-propagations raised by opinion leaders, which can be described as exponential truncated power-law decay function. By estimating the parameters in the model, the initial influence, influence decay rate and influence insistency of opinion leaders can be evaluated quantitatively. Results of the experiment based on the data collected from Sina microblog, show the total retweeted messages is weakly correlated to the number of opinion leaders in the spread process. In addition, the number of followers possessed by opinion leaders is positively correlated to the power of their initial influence. However, it exhibits no correlation with the decay rate and insistence time of the influence. The efficiency and correctness of the proposed model are validated by predicting the spread trends of hot messages in actual microblog networks, which is important to network marketing and message propagation controls.