Urban traffic congestion remains a pressing challenge in Erbil, particularly at signalized intersections where delays contribute to fuel consumption, emissions, and commuter frustration. This study presents a calibrated microsimulation model using PTV VISSIM to replicate field-measured control delays at a key intersection in Erbil. Field data were collected through video-based observations and analyzed to establish baseline performance. The simulation was calibrated using manual adjustments to driver behavior and signal timing parameters, constrained by the student version of the software. The model's accuracy was evaluated through statistical comparison with field data. Results showed a strong correlation (R=0.938) and a high coefficient of determination (R2=0.879), indicating that nearly 88% of the variation in simulated delay could be explained by observed conditions. Error metrics further supported the model's reliability, with a root mean square error (RMSE) of 7.31 seconds per vehicle, a mean absolute error (MAE) of 5.92 seconds, and GEH statistics consistently below 2, well within accepted thresholds for traffic modeling. While the study was limited to a single intersection due to software constraints, the findings offer practical insights for traffic engineers and policymakers. Recommendations include adopting adaptive signal control systems and integrating intelligent transportation technologies to improve intersection performance. Future research should expand the model to multiple intersections, incorporate real-time data, and explore environmental impacts. This study provides a localized, data-driven foundation for improving urban mobility in Erbil through simulation-based planning.