<p>This study examines the role of disclosed risk information in financial reports and its impact on users' understanding of firms' risk states. It proposes a model to assess risk disclosure quality based on the alignment between disclosed risks and actual firm risk states. A hidden Markov model (HMM) is employed to analyze and predict risk disclosure patterns in annual financial reports of 150 Iranian firms listed on the Tehran Stock Exchange from 2013 to 2019. The model evaluates the probability of alignment between disclosed risk information and actual firm risk states, independent of disclosure decisions. Data from 2020 to 2022 were used to assess the model's predictive accuracy. Results show that variables such as beta coefficient, stock return volatility, foreign revenue share, and operational cash flow volatility positively influence risk disclosure quality, while liquidity, operational leverage, financial leverage, and firm size negatively affect it under certain risk conditions. The predicted average alignment between disclosure level and firm risk state is 43%, suggesting that risk disclosures often fall short of fully reflecting actual risk states. This study offers a novel approach to assessing risk disclosure quality by leveraging quantitative financial data and firm characteristics, reducing subjectivity in evaluation. Unlike traditional methods, it highlights the dynamic relationship between risk disclosures and firm risk states, providing valuable insights for investment and credit decisions.</p>