Existing literature and research findings indicated that cost monitoring and control of construction projects by contractors at the level of site operations has remained ineffective largely due to inability of existing control systems to accurately predict when, to what extent and why an on-going operation or project is to overrun its planned duration and cost. In most cases the information that would enable such advance detection becomes available to decision makers after the affected operation or project is completed. It is then hoped that the information could be used to 'control' future similar situations which in the case of construction projects hardly arise, at least never under identical circumstances. The existing cost control systems also fail to enable rational corrective decisions to be formulated. This resulted in total reliance on previous experience and personal intuition to make a guess of corrective measures. Most research efforts have focussed mainly on various aspects of project modelling and cost control using traditional accounting approaches that consistently fail to meet the requirements and schedule of timely cost control. This research identified, from empirical evidence, construction and management science literature, the essential criteria and features of an effective cost monitoring and control approach for construction projects. The evidence from these three sources led to the formulation of an alternative approach based on quantitative analysis of cost data from construction projects. The cost monitoring and control process carried out on sites was formulated as a problem whose solution process is implemented using multiple regression and goal programming models and techniques that enable timely evaluation and prediction of costs and a rational computation of corrective decisions. This allowed cost deviations to be detected and optimum corrective measures calculated while the affected operation or project was still in progress.