The PROGRESS series aims to improve the development, validation, and clinical application of prognostic models. Prognostic models use multiple factors to predict future clinical outcomes in individual patients. These models are crucial for informing clinical decisions, improving patient outcomes, and guiding treatment. However, many models are not used in clinical practice due to issues with validation, impact studies, and reporting. Prognostic models are developed using statistical methods, often from cohort studies, and validated with independent data. External validation is essential to ensure models are reliable outside their original context. Models must be validated and tested for their impact on clinical practice and patient outcomes. Impact studies are needed to assess how models influence decision-making, patient outcomes, and healthcare costs. Prognostic models should be developed using large, high-quality datasets, with sound statistical analysis plans. They should be validated in independent datasets and updated when new data or markers become available. Models should be easy to use and accessible, such as through web tools. Examples include the Nottingham Prognostic Index for breast cancer and the Manchester Triage System for emergency care. Prognostic models are important for clinical practice, research, and health services. They help in stratifying patients, guiding treatment decisions, and improving the design of randomized trials. However, many models lack proper validation and impact studies. There is a need for better reporting standards, collaboration between research groups, and ongoing model updates. Recommendations include improving the quality of model development, ensuring external validation, and conducting impact studies. Prognostic models should be used in clinical practice only if they are validated and have demonstrated clinical impact. Future research should focus on updating models, incorporating new biomarkers, and improving the reporting of model development and validation. The PROGRESS series provides a framework for improving prognosis research and its application in clinical practice.The PROGRESS series aims to improve the development, validation, and clinical application of prognostic models. Prognostic models use multiple factors to predict future clinical outcomes in individual patients. These models are crucial for informing clinical decisions, improving patient outcomes, and guiding treatment. However, many models are not used in clinical practice due to issues with validation, impact studies, and reporting. Prognostic models are developed using statistical methods, often from cohort studies, and validated with independent data. External validation is essential to ensure models are reliable outside their original context. Models must be validated and tested for their impact on clinical practice and patient outcomes. Impact studies are needed to assess how models influence decision-making, patient outcomes, and healthcare costs. Prognostic models should be developed using large, high-quality datasets, with sound statistical analysis plans. They should be validated in independent datasets and updated when new data or markers become available. Models should be easy to use and accessible, such as through web tools. Examples include the Nottingham Prognostic Index for breast cancer and the Manchester Triage System for emergency care. Prognostic models are important for clinical practice, research, and health services. They help in stratifying patients, guiding treatment decisions, and improving the design of randomized trials. However, many models lack proper validation and impact studies. There is a need for better reporting standards, collaboration between research groups, and ongoing model updates. Recommendations include improving the quality of model development, ensuring external validation, and conducting impact studies. Prognostic models should be used in clinical practice only if they are validated and have demonstrated clinical impact. Future research should focus on updating models, incorporating new biomarkers, and improving the reporting of model development and validation. The PROGRESS series provides a framework for improving prognosis research and its application in clinical practice.