Performance appraisal refers to the process of performance measurement, assessment, valuation, and judgement over time. Performance ranking based on several criteria of different values is possible only when multi-criteria decision models are adopted. In this regard, different indicators are used in accordance with the type of ranking. Accordingly, inspired by the support vector machine model (SVM) and the Promethee technique, the present study aimed to develop a performance appraisal model for mutual funds and rank them accordingly. In this study, 34 mutual funds accepted in Iran’s capital market were selected during 2016-2018 using the systematic random sampling method. First, the key performance indicators were detected using the indicators of post-modern portfolio theory, which were then approved by managers, experts, and professionals. Then some information about each indicator was collected, and the experts and professionals’ comments were used to weight the indicators and specify the importance and priority of each indicator. Afterwards, an applied model was developed to represent the indicators effective in ranking mutual funds. Finally, the SVM model and the Promethee technique were adopted to rank the concerned mutual funds. The findings revealed that, in comparison to the indicators of downside risk and Sortino, upside potential ratio has the greatest effect on the performance appraisal of the mutual funds accepted in Iran’s capital market.