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Risk is a potential event that leads to loss or harm in software projects. Risks may be classified into negative or positive; where negative risks specifically lead to loss or harm, while positive risks represent a new opportunity in the project. To handle these kinds of risks, risk assessment models and techniques have been introduced. In this paper, we review the most popular and applicable risk assessment models available in the literature. We come up with a taxonomy in which those models can be categorized as: (1) Artificial Intelligence (AI) based, (2) Classical (or Non-AI based), and (3) other Hybrid models. We propose evaluation criteria which have been used to compare these models. After analyzing evaluation results, we recommend suitable models which can be used to avoid project risks.