CeriBell, Inc.

CeriBell, Inc. (CBLL) Price Prediction & Forecast

$23.730

+0.365 (+1.54%)At close

Price Predictions

1-Day Price Prediction
-1.71%
1-Week Prediction
+2.49%
1-Month Prediction
2026 Prediction
2030 Prediction

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CBLL Prediction & Forecast by Similar Chart Analysis

Alphio's CBLL stock price prediction model matches the current CeriBell, Inc. tape against historical breakout patterns, then publishes 1-day and 1-week targets first. The 1-day print is $23.32 (-1.71%). The 1-week path is $24.32 (+2.49%). Longer windows use the same pattern set plus seasonality; the 1-month and multi-year forecasts sit behind unlock because they include precise min / avg / max bands.

Should I Buy CeriBell, Inc. Stock?

CeriBell Inc is a good buy right now due to its recent revenue growth of 33% year-over-year in Q2 2026, reaching $28.1 million, and a high gross margin of 92%. The stock is currently priced at $23.73, which is below the analyst target of $26, indicating potential upside. However, the main risk is the widening net loss of $19.3 million in Q2, which could impact investor sentiment.

CBLL stock price ended at $23.73 on Friday, after rising +1.54%

CeriBell, Inc. (CBLL) last closed at $23.73, gaining +1.54%. These facts feed the 1-day and 1-week CBLL price prediction above.

Forecast Drivers

CeriBell, Inc. (CBLL) forecast drivers combine similar chart patterns, seasonality, and moving averages.

Similar patterns

Positive

Bullish

Seasonality

Negative

Bearish

SMA 20

Positive

Bullish

SMA 200

Positive

Bullish

Similar Chart Patterns

Stocks whose recent price path most closely matches CBLL, ranked by similarity.

Seasonality analysis for CBLL

Historically the probability of a positive August return for CBLL is 34.15%. December offers the highest probability of a positive month at 48.84%, while February is the weakest seasonal window. Alphio blends this calendar with technical signals and similar chart pattern matching before it writes the forecast.

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This page is for research only and is not investment advice. Models can be wrong. Past performance does not guarantee future results.

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