Development of Multi-Electrode Arrays (MEA) enables researchers to record multiple spike trains simultaneously from associated neurons. Simultaneously recorded multiple spike trains are used to study how groups of neurons process information and how they interact with each other. Developing a statistical method for analyzing multiple spike trains and, in particular, estimating the functional connection between spike trains is a challenging problem that has resulted in substantial research. In this study a statistical method, the Cox method is presented for analyzing functional connection of simultaneously recorded multiple spike trains. This method estimates a vector of influence strengths from multiple spike trains (called reference trains) to the selected (target) spike train. Selecting another target spike train and repeating the calculation of the influence strengths from the reference spike trains enables researchers to find all functional connections among multiple spike trains. In order to study functional connection an ‘influence function’ is identified. This function recognizes the specificity of neuronal interactions and reflects the dynamics of postsynaptic potential. The Cox method has been thoroughly tested using multiple sets of data generated by the neural network model of the leaky integrate and fire neurons with a prescribed architecture of connections. The results suggest that this method is highly successful for analyzing functional connection of simultaneously recorded multiple spike trains.