Psychometric quality analysis of psychological instruments was important to ensure credible measurement. This study aims to compare the psychometric quality analysis of multiple-choice test items using three different applications to evaluate the advantages and disadvantages of the features provided in supporting classical test theory analysis. This study used a quantitative approach by analysing dichotomous data from 50 participants of a 30-item multiple-choice test. The data were analysed using three applications (AnBuso, Iteman, and R) to compare the statistical output of the main psychometric parameters of the classical test theory, such as difficulty index, discrimination index, and distractor effectiveness. Data analysis was conducted descriptively and quantitatively by comparing the features provided by the application in support of classical test theory analysis to evaluate the advantages and disadvantages of each application. The study found that all three applications produced similar results for the difficulty index, distractor effectiveness, and discrimination index. AnBuso proved user-friendly but limited in capacity, Iteman offered comprehensive output with restricted free functionality, and R provided flexibility but required programming expertise. The application demonstrated unique strengths that are suitable for different research needs and user proficiencies. The choice of application should consider factors such as analysis complexity, sample size, and user expertise. Further research into paid options and diverse test conditions is recommended for a more comprehensive evaluation of these applications in classical test theory analysis.