Software Project Cost Estimator

Tick the features your project needs, choose how finished the result has to be, and set the hourly rate you expect to pay. The estimator returns an effort range in hours, the budget that range implies at your rate, and a calendar timeline for one developer. The spread between the low and high figures is the point, not a flaw — software estimation is a range discipline, and a tool that hands you a single number is guessing with false confidence. Read the low end as an experienced team hitting no surprises and the high end as a normal amount of friction.

How the estimate is built

Each feature carries an editorial hour range. These are planning numbers drawn from typical agency scoping documents, not quotes, and they are stated in the open so you can argue with them:

The base covers what every project needs before feature work starts: repository and environment setup, data model, framework decisions, a deployable skeleton. Selected ranges are summed and scaled by a complexity multiplier — 0.7 for an MVP, 1.0 for standard, 1.5 for polished:

hours = round((base + Σ features) × multiplier)

Budget multiplies hours by your rate, and the timeline divides hours by 30 productive hours per developer-week, rounding up:

budget = hours × rate

weeks = ⌈hours ÷ 30⌉

With the default boxes — accounts, payments, an API and CI on top of the base, at standard complexity — the sum runs 180 to 310 hours. At $95 an hour that is $17,100 to $29,450, spread over 6 to 11 weeks for one developer working alone.

A short history of estimating software effort

Estimation became a named discipline the moment large teams started missing deadlines badly enough to write about it. Frederick Brooks drew the first widely read lessons from managing IBM's System/360 hardware and then its OS/360 software during the 1960s, and published them in 1975 as The Mythical Man-Month. His target was the unit itself: the man-month, the assumption that people and months trade off freely, so a job needing twelve man-months could be finished in one month by twelve people. Brooks argued this is false for anything with sequential steps and communication overhead, and stated the result now known as Brooks's law: adding manpower to a late software project makes it later.

The first widely adopted way to size software by what it does, rather than how much code it takes, came from Allan Albrecht at IBM, who presented function point analysis at a joint IBM, SHARE and GUIDE symposium in Monterey, California, in October 1979. Instead of counting lines of code, function points count inputs, outputs, inquiries, files and interfaces, giving a measure that does not depend on the programming language. Barry Boehm took the statistical route two years later. His 1981 book Software Engineering Economics introduced the Constructive Cost Model, or COCOMO, fitted by regression on 63 completed projects at the aerospace firm TRW. Its basic equation, in the organic mode meant for small teams on familiar ground, puts effort in person-months at 2.4 times thousands of lines of code raised to the power 1.05, the exponent above one encoding that effort grows faster than size.

Boehm's book also drew the picture that explains why this estimator hands you a range rather than a number. He plotted how far an estimate can miss depending on how early it is made, a shape he called the funnel curve and that Steve McConnell renamed the cone of uncertainty in his 1997 Software Project Survival Guide. Near a project's start, before requirements are pinned down, honest estimates vary by roughly a factor of four in either direction. That width is not incompetence; it reflects the state of knowledge. The same book described Wideband Delphi for group estimation, which Boehm and John Farquhar had adapted during the 1970s from the Delphi forecasting method developed at the RAND Corporation in the 1950s by Olaf Helmer, Norman Dalkey and Nicholas Rescher. That lineage runs to planning poker, which James Grenning defined in 2002 and Mike Cohn popularized in Agile Estimating and Planning in 2005, where teams estimate in relative points precisely because absolute hours resist agreement.

Three stacks priced through

A side project going public needs the base, login and a deploy pipeline, built to MVP standard. Raw hours are 40+30+20 = 90 on the low side and 60+50+40 = 150 on the high, and the 0.7 multiplier brings that to 63–105 hours. A freelancer at $95 an hour lands between $5,985 and $9,975 across 3 to 4 weeks. This is the tier where a weekend project becomes something other people can sign into.

A startup building a paid SaaS matches the defaults: accounts, subscription billing, an API for the frontend and future integrations, CI from day one. Standard complexity, because paying customers see it. That is the 180–310 hour, $17,100–$29,450 estimate above. Worth noticing: payments and auth together are 70–120 of those hours, close to 40% of the project, spent before any feature a customer would actually pay for exists.

A scale-up rebuilding its product checks every box — admin dashboard, mobile app, AI features and all — at polished complexity. Raw hours of 400 to 690 scale by 1.5 to 600–1,035 hours. At a $140 blended agency rate the budget runs $84,000 to $144,900. The single-developer timeline of 20 to 35 weeks is unrealistic at this size; a three-person team compresses it to roughly 7 to 12 calendar weeks, though coordination overhead means never quite dividing by three.

What moves a project between MVP and polished

The multipliers encode a real difference in scope, not just effort. An MVP at 0.7 means the happy path works and little else: errors surface as raw messages, the design comes straight from a component library, edge cases are handled by apologizing, and the admin interface is a database console. Standard at 1.0 adds what paying users force on you — proper error states, responsive layouts, input validation that explains itself, tests on the paths that touch money.

Polished at 1.5 is where cost curves bend. A coherent design system, accessibility passes, loading and empty states for every screen, performance work, observability so the team learns about outages before customers do. The last 20% of visible quality routinely costs 50% more because it multiplies across every feature already built. Teams that budget for standard and demand polished discover this at the worst possible moment.

Why mobile doubles the scope

At 120–200 hours, the mobile line dwarfs everything else, and the reason is that a mobile app is not a feature — it is a second product. Cross-platform frameworks share business logic but not the surrounding work: push notifications, deep links, offline behavior, app store metadata, review cycles that can stall a release for days, and a signing-and-distribution pipeline with no overlap with the web deploy. A native pair of apps pushes past even this range. If the mobile checkbox flips your budget from comfortable to painful, a well-built responsive web app defers the cost and keeps the option open.

What the estimate leaves out

Deliberately excluded: discovery and specification work, which agencies commonly bill as a separate 10–20% engagement before the build; integrations beyond payment processing, each of which can run 15–60 hours depending on the API on the other side; data migration from an existing system; content and copywriting; and maintenance, which typically runs 15–20% of build cost per year once real users depend on the thing. Project management is also outside the ranges — agencies usually add 10–15% for it on top of engineering hours.

The rate field is yours to set against the market you hire in. As of mid-2026, offshore teams commonly bill $25–50 an hour, Eastern European and Latin American shops $40–75, senior freelancers in the US and Western Europe $80–150, and established agencies $120–250 with project management folded in. The $95 default sits at the senior-freelancer midpoint. Whatever the rate, the hour ranges are the part worth debating — a stakeholder who disputes the budget is usually disputing scope without saying so.

The ranges here are editorial planning figures drawn from typical agency scopes, not a quote for any specific project or advice on procurement. See the site disclaimer.

Frequently asked questions

How much does it cost to build an MVP with login and payments?

Using this estimator's ranges, the base plus user accounts plus payments comes to 110–180 raw hours, and the MVP multiplier of 0.7 brings that to 77–126 hours. At $95 an hour the budget is $7,315 to $11,970, over roughly 3 to 5 weeks for a single developer. That covers a working product with the happy path solid and the rough edges left visible.

How many hours does adding a mobile app take?

This estimator budgets 120–200 hours for a mobile app, the largest single line item and often more than the rest of the project combined. Even with React Native or Flutter sharing one codebase, you still pay for platform-specific fixes, push notification setup, app store review cycles and a release pipeline separate from the web deploy.

Why does the timeline assume 30 productive hours per week instead of 40?

Because a 40-hour week never yields 40 hours of feature work. Standups, code review, deployment babysitting, support interruptions and context switching reliably consume a quarter of the week, and agencies scope on 25 to 32 productive hours for exactly this reason. Dividing a 310-hour estimate by 40 predicts 8 weeks; dividing by 30 predicts 11, and the second number is the one that survives contact with a real calendar.

How much do AI features add to a software project?

The range here is 40–80 hours before the complexity multiplier — $3,800 to $7,600 at $95 an hour. That assumes calling a hosted model API with prompt design, streaming responses, rate-limit handling and evaluation of outputs. It does not cover fine-tuning, building retrieval pipelines over large document sets, or the ongoing inference bill, which is an operating cost rather than a build cost.

Is this estimate the same as an agency quote?

No. These are editorial planning ranges assembled from typical agency scoping patterns, useful for sanity-checking a budget before you talk to anyone. A real quote follows a discovery phase where someone reads your requirements, and it will price integrations, data migration and project management that this tool deliberately leaves out. Treat a quote 40% above the high end of this range as a prompt for questions, not proof of overcharging.