What is محاضرات الدكتور محمد الفايد's rating?

محاضرات الدكتور محمد الفايد is rated 4.8 stars across 86 ratings on the Play Store.

Who makes محاضرات الدكتور محمد الفايد?

محاضرات الدكتور محمد الفايد is published by arapp2you, launched on May 06, 2026.

Where does محاضرات الدكتور محمد الفايد rank in its category?

محاضرات الدكتور محمد الفايد ranks #9238 of 33338 apps in Health & Fitness, putting it in the top 27.7% by revenue.

How much does محاضرات الدكتور محمد الفايد earn?

Q: How much does محاضرات الدكتور محمد الفايد earn?

محاضرات الدكتور محمد الفايد earns approximately 229 per month based on bumetric's ML revenue forecast, calibrated against 33338 comparable Android apps in Health & Fitness.

Android app from arapp2you · Health & Fitness

ML forecast ★ 4.8 · 86 Free

~229/mo

ML revenue forecast. Calibrated against 33338 apps in this category.

Confidence band

±15%

High — many comparable apps with verified data

At a glance

Earns 1.53× more than the category median (150/mo).
Ranks #9,238 of 33,338 in Health & Fitness (top 27.7% by revenue).
Launched May 06, 2026.

Where محاضرات الدكتور محمد الفايد sits in Health & Fitness

Revenue distribution of 33338 comparable apps. محاضرات الدكتور محمد الفايد highlighted.

محاضرات الدكتور محمد الفايد vs comparable apps

Revenue trajectory side-by-side. Bold = محاضرات الدكتور محمد الفايد, ghosted = peers.

App spec

Launched

May 06, 2026

Price

Free

Monetization

Free

Comparable Android apps

The five apps in Health & Fitness with the closest revenue to محاضرات الدكتور محمد الفايد. Click any to see its detail page.

App	Revenue	Rating	Ratings
Pregnancy and Baby Tracker	229	★ 3.6	5K
Goodsomnia Lab: Track snoring	229	★ 3.8	158
Swedish Fit	229	—	0
Kiplin	229	—	0
Push-ups Trainer	229	★ 4.7	93

Own محاضرات الدكتور محمد الفايد? Replace our estimate with your real revenue via Stripe Connect or ASC. Get a public Verified badge.

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How we calculated this

Each forecast combines App Store rating, ratings count, monetisation model, pricing tier, IAP signals and ad-supported flag. The base estimate is then multiplied by a per-category scaling factor learned from apps with founder-verified MRR. Every number on this page comes from public APIs and bumetric's own snapshot history.

Full methodology covers input variables, accuracy bands per category and how we treat apps without comparable anchors. See also the live data on محاضرات الدكتور محمد الفايد's tracker page for current rating, reviews and snapshot timeline.

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