510(k) Predicate Finder
Find potential predicate devices for your 510(k) submission. Enter a K-number to find all clearances with the same product code, a three-letter product code to browse clearances directly, or search by device name.
Let the assistant find your predicates
Describe your device and the Research Assistant searches 510(k)s, compares intended use, and drafts a predicate shortlist — with citations.
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Radiological Machine Learning Based Quantitative Imaging Software With Change Control Plan
Radiology
The Radiological Machine Learning Based Quantitative Imaging Software with Change Control Plan is a software-only medical device that employs machine learning algorithms on radiological images to generate quantitative imaging outputs, including view selection, segmentation, and landmarking functions, and is designed with a predetermined change control plan that permits specified modifications to the device's machine learning algorithms over time without requiring a new premarket submission for each update. Classified as FDA Class 2 under regulation 892.2055, it requires 510(k) clearance in the Radiology specialty. The device is not an implant and not life-sustaining.
510(k) Clearances
1 matchesWhat is a Predicate Device?
A predicate device is a legally marketed device that a new 510(k) applicant uses to demonstrate substantial equivalence. The FDA's 510(k) pathway requires manufacturers to show that their device has the same intended use and similar technological characteristics as one or more predicate devices already cleared for commercial distribution.
Finding the right predicate is a critical step in 510(k) strategy. Manufacturers typically search for cleared devices with the same FDA product code, which groups devices by their intended use and regulatory classification. This tool helps you identify potential predicates by browsing all clearances within a product code.
Note that predicate devices must be legally marketed — they cannot be devices that were cleared but never commercialized, or devices subject to a mandatory recall. The determination of substantial equivalence considers intended use, technological characteristics, and performance data.