Choosing the right scikit-learn model for anomaly detection involves understanding dataset structure, dimensionality, and anomaly nature. For low-dimensional Gaussian data, EllipticEnvelope is suitable. For complex data, consider DBSCAN or LOF. High-dimensional datasets benefit from IsolationForest due to its scalability and effectiveness in outlier detection.