Though there is a considerable agreement amongst past studies about the great variability in conflict judgments by Air Traffic Controllers (ATCos), certain behaviors observable in control rooms speak in favor of the existence of a common core they would that controllers share regarding conflict risk perception. The study presented in this paper began with the construction (from real recordings) of traffic scenarios showing two converging aircraft in approach. Three variables characterized these traffic scenarios, quantifying respectively horizontal separation, vertical separation and the momentum of the formation of the judgment (prediction time span). The conditions created by factorial manipulation of three variables led to the design of short scenarios (about 1min) involving two aircraft upon which 161 controllers gave their judgments about possible occurrence of a separation loss. A first descriptive analysis of the data, conducted in Averty (2005), confirmed the large variability of the experts judgments but also clearly indicated the global consistency of the results. The data thus called for a deeper statistical analysis, the results of which will be presented in the article. In a first step, particular models have been constructed for each value of the prediction time span. The comparison of the models parameters allows evaluating the influence of the time span on the conflict perception. It appears for example that the horizontal dimension has more "separating power" that the vertical dimension far from the conflict location, but that its relative importance diminishes (along with uncertainty) as the conflict resolves. Individual models are then nonlinearly aggregated into an "integrated model" by maximum likelihood estimation on the whole dataset. Finally, the relevance of this model to individual models is statistically validated, indicating that very few information has been lost in the aggregation process.