Financial distress of municipalities, although comparable to bankruptcy of private companies, has a far more serious impact on the well-being of communities. For this reason, it is essential to detect deficits as soon as possible. Predicting financial distress in municipalities can be a complex task, as it involves understanding a wide range of factors that can affect a municipality's financial health. In this paper, we evaluate machine learning models to predict financial distress in Italian municipalities. Accounting judiciary experts have specialized knowledge and experience in evaluating the financial performance, and they use a range of indicators to make their assessments. By incorporating these indicators in the feature extraction process, we can ensure that the model is taking into account a wide range of information that is relevant to the financial health of municipalities. The results of this study indicate that using machine learning models in combination with the knowledge of accounting judiciary experts can aid in the early detection of financial distress, leading to better outcomes for the communities.

翻译：市政财务困境虽然与私营企业破产具有可比性，但对社区福祉的影响更为严重。因此，尽早发现赤字至关重要。预测市政财务困境是一项复杂的任务，需要理解影响市政财务健康状况的多重因素。本文评估了用于预测意大利市政财务困境的机器学习模型。会计司法专家在评估财务绩效方面具有专业知识和经验，他们使用一系列指标进行评估。通过将这些指标纳入特征提取过程，可以确保模型考虑了与市政财务健康相关的广泛信息。研究结果表明，将机器学习模型与会计司法专家的知识相结合，有助于早期发现财务困境，从而为社区带来更好的结果。