Highlights•Multi-model order spatially constrained ICA reveals highly replicable group differences and consistent predictive results from resting data of schizophrenia.•Multi-model order ICA provides a comprehensive way to study brain functional network connectivity within and between multiple spatial scales, highlighting findings that would have been ignored in a single model order analysis.•Cross-model order ICA provides useful information and is widely applicable to other areas since it allows us to capture coupling between smaller and larger networks.•Cross-model order ICA study improves classification accuracy in detecting schizophrenia.•Our framework was built and tested leveraging a large N (N > 1,600) dataset, and revealed highly replicable group differences and consistent predictive results across datasets.