January 17, 2022


Predicting Ovulation Using Apps vs. Calendar Methods: A Review

By Katelyn Myers, DO


Editor’s Note: The research article reviewed below is titled, “Can apps and calendar methods predict ovulation with accuracy?” It was published by Johnson et al in 2018 in Current Medical Research and Opinion. Dr. Katelyn Myers, now a resident in obstetrics and gynecology, summarized the research during the FACTS elective. Her thoughtful review will give readers new insights into the utility of charting with fertility awareness-based methods (FABMs) as well as warnings about potential pitfalls if relying on applications (apps) to predict ovulation.


Women in developed countries are delaying pregnancy and often expect to conceive within three to six months. An abundance of fertility applications now aim to identify a woman’s fertile window and day of ovulation, which could presumably help them time intercourse when attempting to conceive.* Few of these apps detail their algorithms, or they operate on the principle of a 28-day cycle and assume ovulation occurs consistently on day 14. Yet, cycle lengths and timing of ovulation vary from woman to woman and from cycle to cycle, a fact that challenges the reliability of these apps to predict ovulation. The study by Johnson et al summarized below tests the accuracy of predicting ovulation by cycle apps compared to various calendar methods.


The 2018 study by Johnson et al had three aims. The first objective was to determine the range of ovulation days for any given cycle length through daily urine collections of luteinizing hormone (LH) from volunteers. Ovulation occurs within one day after the LH surge. This is the ovulation day that serves as a comparison for the other two arms of the study. 

The second aim was to examine whether the apps’ predictions were accurate by comparing the predicted and actual ovulation days. All cycle-tracking calendar apps for iOS and Android were downloaded over ten days in 2017, and simulated cycles were entered into the apps. 

The third aim was to examine the accuracy of the calendar method by using it for all the volunteers and comparing it to the actual ovulation day. Four calendar-based methods were assessed, including the Standard Days Method. A probability table was used for statistical analysis to record the likelihood of ovulation occurring on any given day for the range of cycle lengths.


A total of 768 volunteers and 73 calendar apps were included in the study. The women had a mean age of 32 years and had been trying to conceive for 15 months, on average. According to the LH surge, the highest probability of ovulation was on day 16 for a 28-day cycle, which occurred in 21% of women in the study. However, the apps identified day 15 as the day of ovulation, which only occurred in 19% of women. Similarly, the calendar method uses day 14 as the most likely day of ovulation in a 28-day cycle, which only applied to 14% of the women in this study. 

The apps predicted the day or days of ovulation with accuracies ranging from 33 to 43%. Many of the apps also identified a fertile window that was commonly 10-16 days long. This is associated with only a 65% probability of including the true day of ovulation.


The results of this timely study show that the available fertility apps are not a reliable means to determine a woman’s day of ovulation. This creates a significant problem for the women using these apps. The term “millennial” refers to a group of adults aged 22 to 38 years old, which includes a large percentage of women in their reproductive years. It is very common for this demographic to utilize smart phone apps for multiple areas of life, likely due to the popularity of cellphones during their formative years. It comes as no surprise to see so many fertility apps available that target this group of women. 

Several questions beg to be answered regarding women who rely on these apps to guide their fertility decisions. For instance, how many of them follow the advice of these apps because of the convenience they offer? How long will women try to conceive using the app’s advice before questioning the accuracy of the predicted day of ovulation and fertile window? How many women will download a fertility app before seeking care from a licensed physician or fertility expert?

The time spent trying to conceive becomes delicate because it is now common for women to delay pregnancy, and fecundability is known to decline rapidly as women age. A woman may spend a significant amount of time attempting to conceive based on the information a fertility app provides. Yet, this time could be utilized more efficiently by following a different approach. A woman may be better served by seeing an obstetrician gynecologist (Ob/Gyn) and/or primary care physician trained in fertility awareness-based methods (FABMs) to learn about their window of fertility and address their health, lifestyle, and expectations. Her physician can also assist with infertility, which is diagnosed after one year of unsuccessfully trying to conceive, or after six months if the woman is over the age of 35. 

An Increasingly Popular, Evidence-Based Approach

Fertility awareness-based methods are another reliable option for women to learn to chart their menses, cervical mucus, cycle length, and hormones. These charts can aid in determining if and when ovulation occurs. While working with the healthcare team, a woman can identify her fertile window and determine when to have intercourse if trying to conceive. If women become aware of these options, they may not feel the need to rely on smart phone fertility apps that lack accuracy to predict ovulation.

Study Merits and Limitations 

One strength of this study is the volume of fertility apps and participants that were involved. This strengthens the study results and shows how these apps may not be appropriate for most women to predict ovulation. This research is timely and relevant because these apps are so easily accessible. 

The study also has some limitations. During the second arm of the study, the apps were compared to the actual day of ovulation using urinary LH samples. However, in the third arm, the only FABM that was compared to the actual day of ovulation was the calendar method, which is not nearly as effective as other types of FABMs. Additionally, the FEMM app was included in the comprehensive list of fertility apps, and the Natural Family Planning Fertility Charting for the Creighton Model was released in 2018, after completion of this study. Future research should analyze the FABM apps separately and compare the accuracy of these methods to the other fertility apps.


In summary, it is clear that fertility apps are rising in popularity, with hundreds of apps now available to women. For medical professionals, this highlights the importance of asking during routine appointments if their patients are using these applications. If a woman is using one of these fertility apps, it is valuable to understand why she began using it, how long she has used it, her perception of its accuracy, and whether she has discussed her desire to conceive with a medical professional. This would help physicians and other medical professionals to utilize shared decision making when discussing a woman’s desire to conceive.

*Editor’s Note: Although it would seem that identifying the day of ovulation is critical for couples to time sexual relations when attempting to conceive, those who wait for the day of ovulation to have intercourse may actually lower their probability of conception. A seminal study by Wilcox et al published in the New England Journal of Medicine demonstrated that the highest probability of pregnancy (25-28%) occurs when couples have intercourse 1 or 2 days before ovulation.v On the day of ovulation, the probability of becoming pregnant is less than 10%, plummeting to 0% the day after ovulation. Therefore, it would be more useful for women to learn to chart their cervical fluid secretions—the best indicator of the onset of the fertile window that heralds the arrival of ovulation a few days before it occurs. 


[1]  Johnson S, Marriott L, Zinaman M (2018) Can apps and calendar methods predict ovulation with accuracy?, Current Medical Research and Opinion, 34:9, 1587-1594, DOI: 10.1080/03007995.2018.1475348.

[2]  Balasch J, Gratacós E: Delayed Childbearing: Effects on Fertility and the Outcome of Pregnancy. Fetal Diagn Ther 2011;29:263-273. doi: 10.1159/000323142.

[3]  ACOG Committee Opinion No. 589. (2014). Female Age-related Fertility Decline, 123(3), 719-721. DOI: 10.1097/01.aog.0000444440.96486.61.

[4]  Pallone, S. R., & Bergus, G. R. (2009). Fertility Awareness-Based Methods: Another Option for Family Planning. The Journal of the American Board of Family Medicine, 22(2), 147-157. doi:10.3122/jabfm.2009.02.080038.

[5]  Wilcox AJ, Weinberg CR, Baird DD. Timing of sexual intercourse in relation to ovulation. Effects on the probability of conception, survival of the pregnancy, and sex of the baby. N Engl J Med. 1995;333(23):1517-1521. doi:10.1056/NEJM199512073332301.

About the Author

Katelyn Myers, DO

Katelyn Myers, DO wrote this review as a fourth-year medical student and is now a resident physician in obstetrics and gynecology. She had this to say about the FACTS course: “The FACTS elective taught me about fertility awareness-based methods, which is not routinely taught in the medical school curriculum. I am glad that I am familiar with the different types of FABMs because it will allow me to serve my future patients better.”

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