Background <p>Research on the development of prognostic biomarker-based models for genetic neurodegenerative diseases lacking disease-modifying treatments is advancing rapidly. Currently, prognostic models are being developed to predict individual disease onset and progression rates for Huntington’s disease, spinocerebellar ataxia type 1, and spinocerebellar ataxia type 3. These models have potential applications in research, such as evaluating onset-delaying treatments and their timing, and in clinical practice, where they may offer personal utility to mutation carriers. However, the perspectives of healthcare professionals in genetic counselling have not yet been adequately explored.</p> Methods <p>In this qualitative interview study, we interviewed 18 Dutch healthcare professionals in genetic counselling, representing the majority of the Dutch counselling practice for these conditions, to explore their views on using onset and progression predictions in clinical practice.</p> Results <p>Healthcare professionals highlighted potential benefits, such as reducing uncertainty and supporting informed life and family planning, which are among the pivotal reasons for mutation carriers to opt for predictive genetic testing. They also noted possible drawbacks, including psychological distress for mutation carriers, discussed challenges in defining clinical disease onset, and some questioned the degree of personal utility of these predictions. Finally, healthcare professionals emphasised several key conditions for implementing such prognostic models, including sufficient predictive accuracy, a narrower and more precise age range, and the need for additional counselling.</p> Conclusion <p>This study provides insights in the perspectives, views, and concerns of the majority of healthcare professionals in the Dutch counselling practice regarding the use of onset and progression predictions. Healthcare professionals identified several potential benefits and drawbacks of onset and progression predictions and discussed the conditions necessary for their implementation. During model development and before clinical implementation, clarity is needed on how disease onset is defined in the model and what constitutes sufficient model performance. Furthermore, aligning the model with its intended goals, such as providing personal utility, and assessing the feasibility of achieving meaningful predictions are important steps.</p>