Monro (MNRO) EBITDA (2010 - 2025)
Monro (MNRO) posted EBITDA of $33.86 million for fiscal Q3 2026 (quarter ended Dec 27, 2025), up 25.0% from $27.09 million a year earlier and up 20.8% from the prior quarter.
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Analysis
Monro (MNRO) EBITDA (2010 - 2025) Analysis & Trends
For the trailing twelve months through Dec 27, 2025, EBITDA at Monro was $64.56 million, down 44.8% year-over-year; for FY2025 (ended Mar 29, 2025), it came in at $81.94 million, down 43.0% from FY2024.
- Annual EBITDA has declined for three consecutive fiscal years, with a five-year compound annual growth rate of -13.2% (FY2020 to FY2025).
- In prior fiscal years, Monro's EBITDA was $143.63 million in FY2024 (-8.4%), $156.79 million in FY2023 (-14.1%), $182.47 million in FY2022 (+22.0%) and $149.54 million in FY2021 (-10.3%).
- The fiscal Q3 2026 figure stands as the highest quarterly EBITDA since fiscal Q3 2024.
- On a year-over-year basis, EBITDA increased in two of the last seven quarters, with an average decline of 15.6%.
- The strongest year-over-year quarter for EBITDA in the past five years was fiscal Q4 2021, with growth of 123.9%; the weakest was fiscal Q1 2026, with a decline of 69.3%.
- According to Business Quant data, EBITDA for the three prior fiscal quarters was $28.03 million (Q2 2026), $9.52 million (Q1 2026) and -$6.84 million (Q4 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | EBITDA (Qtr) |
|---|---|---|---|---|---|
| 1 | Amazon Com | 2,828.15 Bn | 2,344.85 Bn | 104.83 Bn | 47.45 Bn |
| 2 | Home Depot | 312.02 Bn | 305.26 Bn | 16.12 Bn | 7.95 Bn |
| 3 | Tjx Companies | 160.78 Bn | 138.32 Bn | 5.07 Bn | 2.33 Bn |
| 4 | Lowes Companies | 109.83 Bn | 102.79 Bn | 8.58 Bn | 4.20 Bn |
| 5 | Ross Stores | 74.49 Bn | 57.42 Bn | 2.12 Bn | 1.24 Bn |
| 6 | O Reilly Automotive | 73.51 Bn | 72.60 Bn | 2.52 Bn | 1.13 Bn |
| 7 | Target | 69.38 Bn | 63.97 Bn | 8.94 Bn | 3.34 Bn |
| 8 | Autozone | 52.02 Bn | 50.92 Bn | 2.52 Bn | 1.09 Bn |
| 9 | Carvana | 42.62 Bn | 33.11 Bn | 1.38 Bn | 753.00 Mn |
| 10 | Monro | 427.18 Mn | 389.37 Mn | - | - |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Dec 27, 2025 | 33.86 Mn |
| Sep 27, 2025 | 28.03 Mn |
| Jun 28, 2025 | 9.52 Mn |
| Mar 29, 2025 | -6.84 Mn |
| Dec 28, 2024 | 27.09 Mn |
| Sep 28, 2024 | 30.70 Mn |
| Jun 29, 2024 | 30.99 Mn |
| Mar 30, 2024 | 28.11 Mn |
| Dec 23, 2023 | 39.29 Mn |
| Sep 23, 2023 | 40.50 Mn |
| Jun 24, 2023 | 35.74 Mn |
| Mar 25, 2023 | 25.01 Mn |
| Dec 24, 2022 | 42.69 Mn |
| Sep 24, 2022 | 42.73 Mn |
| Jun 25, 2022 | 46.36 Mn |
| Mar 26, 2022 | 32.18 Mn |
| Dec 25, 2021 | 47.63 Mn |
| Sep 25, 2021 | 54.46 Mn |
| Jun 26, 2021 | 48.20 Mn |
| Mar 27, 2021 | 40.43 Mn |
API Access
Monro EBITDA API
Pull this series into your own models, spreadsheets and apps with the Business Quant
Historical Metrics API. The request below matches the chart above — change the
frequency, period or values and it follows. Swap YOUR_API_KEY for your own key.
https://data.businessquant.com/historic?slug=ebitda&ticker=MNRO&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "ebitda", "ticker": "MNRO", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=ebitda&ticker=MNRO&period=max&api_key=YOUR_API_KEY");
const data = await res.json();