As the world transitions toward more sustainable energy sources, there is an increased interest in renewables, with offshore wind well placed to provide significant grid-scale input. Historically, a key limitation has been the cost, with the first offshore wind farms in Europe costing $175 to $250 per megawatt-hour (MWh). Industry developments have resulted in this coming down to $60 to $70 per MWh. Improved geotechnical design methods have contributed to this reduction by optimizing foundation design and reducing steel requirements. Further CAPEX lowering associated with the reduction in geotechnical risk (and associated costs such as drill standby and hammer requirements) during installation are considered possible with improved pile installation prediction. There are currently no standardized methods for modeling the installation of monopiles. Companies typically use published research based on jacket piles or smaller test piles or in-house methods derived from past project experience. This has led to inaccurate predictions thought to be associated with the difference in size between jacket/test piles and monopiles; in addition, predictions from different companies often vary significantly. Thus, decision makers often have low confidence in such predictions, which often leads to conservative decision-making during installation. This may result in the use of larger-than-necessary hammers or driving-induced fatigue predictions, or both, and the inclusion of standby drilling rigs. This paper is based on the back analysis of over 200 monopile installation records covering different projects, pile geometries, and varied geologies. This allowed a detailed review of prediction methodologies and a revised understanding of how the predictions are affected by the engineering properties of the soil. Several interruptions were noted within the driving records, enabling an evaluation of how the observed setup for monopiles compares to previously published records for jacket piles. A new model was then developed to cover the assessment of installation interruptions for large-diameter piles.