This research aims to evaluate the effectiveness of concurrent calibration in constructing an item bank for the "Contemporary Trends in Psychology" course within unidimensional Item Response Theory (IRT) models (Rasch, 1PL, 2PL, 3PL, 4PL), and to identify the most suitable model. It also seeks to reveal the final psychometric properties of the item bank based on the selected model after purifying items and persons. The sample consisted of 1165 students from Zagazig University, who completed 481 initial items. The research employed a descriptive analytical approach, comprising two stages: classical item analysis (CTT) to remove 19 negative items, resulting in 462 items, and an Item Response Theory (IRT) analysis with concurrent calibration. Concurrent calibration showed significant effectiveness with Rasch, 1PL, and 2PL models, but faced computational difficulties with 3PL and 4PL models due to large data size. Comparing the successful models, the Two-Parameter Logistic Model (2PLM) was identified as the most suitable; it showed a good fit for 351 items (76%) and excelled in overall model fit indicators (AIC, BIC, HQ, logLik). This superiority is attributed to the 2PLM's ability to estimate both difficulty and discrimination parameters for each item, providing a more accurate description of item characteristics. The final psychometric properties of the item bank, after item and person purification, indicated that high discrimination values signify the bank's clear ability to differentiate between individuals of varying abilities. These results confirm that the developed item bank possesses strong psychometric properties, ensuring the accuracy and reliability of measurement in educational and psychological assessments.