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How much does Aajnodin earn?

Android app from Aliasgar Sk Fakhruddin · Social

ML forecast ★ 4.4 · 7K Free

~917/mo

ML revenue forecast. Calibrated against 23165 apps in this category.

Confidence band
±15%
High — many comparable apps with verified data

At a glance

What the app looks like

Live screenshots from the Play Store, captured by our snapshot worker. Tap any image to enlarge.

Aajnodin screenshot 1 Aajnodin screenshot 2 Aajnodin screenshot 3 Aajnodin screenshot 4

Aajnodin's revenue trajectory

Forecast revenue from snapshot history. Last 1 months.

Where Aajnodin sits in Social

Revenue distribution of 23165 comparable apps. Aajnodin highlighted.

Aajnodin vs comparable apps

Revenue trajectory side-by-side. Bold = Aajnodin, ghosted = peers.

App spec

Version
2.79
Last update
Dec 27, 2025
Launched
Jun 23, 2014
Price
Free
Monetization
Free

What Aajnodin actually does (from store listing)

Aajnodin app is the original app developed by Aliasgar Sk. Fakhruddin of www.aajnodin.com. This app has been launched for mobile users who want to access the information provided on the website offline. Most of the sections have been provided offline except downloads which would otherwise increase the app size. The features provided in the app includes 1. Aqa Maula TUS Current Qiyaam Shareef 2. Namaz Timings with Change City (Works Offline) with Azan 3. Todays Miqaat 4. Todays Aamal Du…
Read full description →

Comparable Android apps

The five apps in Social with the closest revenue to Aajnodin. Click any to see its detail page.

AppRevenueRatingRatings
Unfollow Analyzer - Unfollower icon Unfollow Analyzer - Unfollower 918 ★ 3.9 7K
씀 : 일상적 글쓰기 icon 씀 : 일상적 글쓰기 919 ★ 4.6 10K
HelloParent: School Parent App icon HelloParent: School Parent App 920 ★ 3.7 9K
Love images and messages App icon Love images and messages App 920 ★ 4.5 6K
InterNations icon InterNations 914 ★ 3.2 10K
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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 Aajnodin's tracker page for current rating, reviews and snapshot timeline.

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