Gi point processes have been used as point patterns models, specially those with inhibition, which show more regularity than completely random processes. These models incorporate both spatial inhomogenity and dependence between points. For a given point pattern, assume that it is conforming of Gi process then our aim is to estimate model parameters. It is generally difficult to evaluate and maximize the likelihood of point processes. Even simple exponential family models such as the pairwise interaction processes including a normalizing constant which is an interactable function of ??. An alternative to the likelihood function is the pseudolikelihood function. Our involved method is the maximum pseudolikelihood method, although we discuss also the maximum likelihood method, partly. Here, Berman-Turner method for finding maximum pseudolikelihood estimate (MPLE) of Gi point processes with exponential condition intensity function are described.