Drilling expenses are a persistent concern for the majority of oil exploration and production companies. Despite declining oil prices, drilling costs continue to rise over time due to inflation and industry demands for more complex unconventional and deeper wells to meet production needs. From the inception of the oil industry, penetration rate has been considered a crucial element in cutting down drilling expenses. Oil companies endeavor to enhance rate of penetration through various strategies, including the implementation of new drilling technologies, optimization of drilling fluids, underbalanced drilling and managed pressure drilling, as well as trajectory and parameter optimization. However, due to the complexity in predicting rate of penetration directly, evaluating these methods successfully without field trials within similar geological formations poses a significant challenge. This introduces additional cost risks without guaranteeing success. Therefore, conducting field trials becomes essential for selecting an optimal scenario and driller will perform various drill-off tests by varying multiple sets of parameters. The process itself is resource-intensive and time-consuming, and the driller needs to have prior experience within the same field. Therefore, a more practical approach to predicting and optimizing rate of penetration while minimizing additional costs and risks without guaranteed success is necessary. This research evaluates a modern rate of penetration simulator for prediction and optimization using a case study of a horizontal well in Kuwait. The development plan for the targeted reservoir is to drill similar horizontal parallel wells, hence there is a valuable opportunity for rate of penetration optimization, due to the homogenous lithology and properties from nearby wells. A successful model was obtained that provided very close results to the real case results with only 0.1% cumulative rate of penetration absolute percentage error, 17.9% rate of penetration mean absolute percentage error, 15.4% weighted mean absolute percentage error, 0.93 drilling time coefficient of correlation and 0.87 drilling time coefficient of determination. Various methods were evaluated to determine the optimum rate of penetration. Final results indicate an opportunity to increase rate of penetration by 33% and prove that there is a chance of achieving an optimum rate of penetration that tends to reduce drilling costs by 18%.