A probabilistic decision-making method for available transfer capability（ATC）considering the existing system conditions in the electricity market is presented. The relationships among the existing power generation dispatches， load curtailment and ATC are quantified economically with an objective of maximizing composite benefits. The non-sequential Monte-Carlo simulation is used to solve the probabilistic problems. For each feasible system state that is generated stochastically， a linear programming model is constructed and solved by the primal-dual interior-point method with infeasible initial points. The ATC probability distribution is obtained through the simulation， based on which a decision-making model considering tradeoff between benefits and risks is established. To determine the probabilistic optimal ATC， a sequential searching algorithm combined with interpolation technique is used. Analysis results on the IEEE RTS demonstrate the validity of the method.