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The research aims at developing an integrated mathematical spreadsheet modelling approach for the practical solution of the stochastic crashing problem in construction project planning. The proposed project crashing methodology is founded upon a synthesis of traditional PERT/CPM network scheduling, Monte Carlo simulation, and linear programming. The main contribution of the introduced model to the existing project management literature is that it produces frequency histograms and relevant statistics for optimum project crash make span and additional cost for project compression, by assuming uncertainty and correlation simultaneously for both normal and crash durations and direct expenses of project activities. The implementation of the model is automated in Microsoft Excel^© through VBA coding. The research is anticipated to assist built environment academics and professionals to improve decision-making effectiveness in the planning of construction projects.