1. A system comprising: a processor; a communication interface in communication with the processor; and a memory in communication with the processor, the memory comprising a prediction tool executed by the processor, the prediction tool including: a cost estimation model configured to generate a predicted cost estimate for performing a first project having a first workscope; and instructions for execution by the processor, the instructions causing the processor to, when executed by the processor: receive, via the communication interface, project data for the first project that includes worker tasks and requirements that define the first workscope; and store in memory the project data for the first project; determine baseline data for developing the cost estimation model, the instructions causing the processor to: apply the cost estimation model to the project data stored for the first project to generate the predicted cost estimate for performing the first project; collect actual cost data via the communication interface that represents an actual cost for performing the first project; and determine a cost difference between the predicted cost estimate and the actual cost for performing the first project; develop the cost estimation model by calibrating the cost estimation model responsive to the baseline data including the cost difference; continue to obtain baseline data and develop the cost estimation model responsive to additional projects until the cost estimation model has reached steady state by: 1) causing the processor to perform a baselining iteration configured to, for each specific project among the additional projects: apply the cost estimation model to that specific project to generate a predicted cost estimate for performing that specific project; collect project actual cost data via the communication interface that represents actual cost of that specific project; and determine a cost difference between the predicted cost estimate for performing that specific project and the actual cost of that specific project; and 2) after the baselining iterations, calibrating the cost estimation model responsive to the baseline data obtained during the baselining iterations including the cost differences for the specific projects; after the steady state is reached, determine a second project with a second workscope that is different than the first workscope, and for which the processor will execute the cost estimation model of the prediction tool in the memory; determine that there is commonality between the first workscope for the first project and the second workscope for the second project; responsive to determining that there is commonality, transfer the baseline data to the second project to create a baseline foundation for baselining the second workscope, thereby allowing the processor to more quickly complete a baselining period for the second workscope and thereby improving baselining efficiency for the second workscope by reducing resource expenditure including baselining processing time for the second workscope in connection with processor execution of the cost estimation model of the prediction tool in the memory for the second workscope; create an offer for performing the second project, the offer obtained by application of the cost estimation model after calibration to the second project; and communicate the offer to a recipient through the communication interface.