Flo’s period predictions become reasonably accurate after about three months of use, with the app predicting future cycle start dates within a 1.26-day error window on average by the third recorded cycle. That’s solid for a calendar-based tracker, but the picture gets more complicated when you look at ovulation and fertility predictions, where app-only methods have significant limitations.
Period Predictions Improve Quickly
Flo uses machine learning to refine its predictions based on the data you feed it. When you first sign up, you enter basic information like your age, weight, and recent cycle dates. The app then estimates your next period, but those early predictions are rough because the algorithm doesn’t yet know your personal pattern.
By your third cycle on the app, predictions tighten considerably. A large-scale study using Flo’s own user data found the average prediction error dropped to 1.26 days by that point, meaning the app was typically off by about a day in either direction when estimating period start dates. The more consistently you log your period start and end dates, the better this gets. If you skip months or forget to log, the algorithm has less to work with and accuracy suffers.
Ovulation Estimates Are Less Reliable
This is where expectations need adjusting. Flo estimates your fertile window based on cycle length patterns, essentially using a calendar method enhanced by AI. It does not measure what’s actually happening in your body on a given day. A 2018 study found that the accuracy of ovulation estimates from menstrual cycle apps that rely solely on user-inputted dates, without hormone measurements or temperature tracking, was generally no higher than 21%.
That’s a significant gap. Ovulation doesn’t always happen on the same cycle day, even in people with regular periods. Stress, illness, travel, sleep changes, and dozens of other factors can shift ovulation by several days within a single cycle. An algorithm looking at your past cycle lengths simply cannot detect these real-time shifts.
Apps that incorporate basal body temperature readings or data from hormone test strips perform meaningfully better at pinpointing ovulation. Flo does allow you to log BBT and other symptoms, which can help the algorithm refine its window somewhat, but the app isn’t using a connected thermometer or hormone reader to verify ovulation the way dedicated fertility monitors do. If you’re relying on Flo to either achieve or avoid pregnancy, that distinction matters.
What Flo Does Well
Where Flo has stronger evidence behind it is in improving how well users understand their own cycles. A pair of randomized controlled trials conducted with researchers affiliated with Johns Hopkins tested the app’s effects over three months. One trial enrolled 321 people who track their cycles, and a second enrolled 117 people dealing with PMS or PMDD symptoms. Both groups showed significant improvements in menstrual health literacy, general well-being, and feelings of control over their health by the end of the study period. The PMS/PMDD group also reported reduced symptom burden and fewer days missed from work or school.
In practical terms, Flo works well as a health awareness tool. Logging symptoms daily helps you spot patterns you might otherwise miss, like mood changes that consistently appear a week before your period, or headaches that correlate with certain cycle phases. That kind of self-knowledge is genuinely useful, and the data backs it up.
Irregular Cycles Pose a Challenge
If your cycles are unpredictable, Flo’s accuracy drops. The algorithm relies on pattern recognition, and irregular cycles by definition lack a consistent pattern. People with conditions like PCOS, thyroid disorders, or perimenopause often have cycles that vary by weeks, which makes calendar-based prediction unreliable regardless of how sophisticated the AI is.
Flo has introduced tools that flag potential health concerns based on user data, including a PCOS risk assessment feature. However, experts have raised concerns about these diagnostic-style features. The app hasn’t published high-level clinical studies validating them, and physicians have pointed out that conditions like PCOS require a full clinical picture, including blood work and sometimes imaging, that a symptom-tracking app can’t replicate. An app noticing your cycles are irregular is useful information to bring to a doctor, but it’s not a diagnosis.
Privacy and Data Security
Period tracking apps collect deeply personal health data, and Flo has had a complicated history on this front. The company faced an FTC settlement in 2021 over sharing user health data with third-party analytics firms after promising it wouldn’t. Since then, Flo has invested heavily in rebuilding trust. It became the first period and ovulation tracker to earn both ISO 27001 (information security) and ISO 27701 (privacy management) certifications, which are internationally recognized standards that require independent audits of data protection practices. The ISO 27001 certification covers 14 domains of security, and the ISO 27701 certification specifically addresses compliance with GDPR and other privacy regulations.
Flo also introduced an “Anonymous Mode” that lets you use the app without attaching your name, email, or other identifying information to your health data. Whether these measures fully address user concerns depends on your personal comfort level, but the certifications represent a higher standard than most competing apps have pursued.
The Bottom Line on Accuracy
For tracking when your period will arrive, Flo performs well after a few months of consistent logging, typically landing within a day or so of the actual start date for people with relatively regular cycles. For ovulation and fertility tracking, the app’s estimates are a rough guide at best. Calendar-based predictions, even AI-enhanced ones, catch the actual ovulation day only about one in five times when no physiological measurements are involved. If pregnancy planning or prevention is your goal, pairing the app with ovulation test strips or a BBT thermometer will give you substantially better information than the app’s estimates alone.