XRP price lost a lot of steam on October 9, dropping to $1.4 following a broader sell-off, and our machine learning algorithm believes the losses are likely to extend throughout the rest of the month.
As Finbold’s AI prediction agent projects, XRP could end the month with a 5.12% correction and trade at $1.33 on Halloween, October 31.

Machine learning algorithm sets XRP price on October 31, 2026
The artificial intelligence (AI) models used in the prediction forecast a relatively narrow price range.
Notably, DeepSeek Chat expects XRP to reach $1.33, while Gemini 3.5 Flash projects a lower price of $1.29. ChatGPT-5.7 Luna is the most optimistic of the three, forecasting XRP at $1.37 by the end of October.
In other words, the gap between the highest and lowest predictions is just $0.08, suggesting that the three models cluster around the same general price range.

AI XRP price prediction on October 31. Source: Finbold
October XRP price outlook
XRP’s latest decline was a result of a broader crypto market downturn, with XRP tracking Bitcoin (BTC) lower amid rising geopolitical risks and institutional withdrawals from spot Bitcoin ETFs, which recorded $244 million in outflows on October 8.
Widespread altcoin weakness and a technical breakdown below key moving averages, of course, added further pressure. From a technical perspective, the asset fell below its 50-day exponential moving average (EMA) near $1.42, a level that had previously provided support. What’s more, the breakdown coincided with a 30.7% increase in trading volume to $4.02 billion, suggesting stronger selling activity.

Overall, XRP’s ability to hold support at $1.32 will be critical in the near term. Namely, a successful defense could trigger a recovery toward $1.5, while a breakdown may expose the 200-day moving average near $1.28.
The next major macroeconomic catalyst is the U.S. Consumer Price Index (CPI) report for September, scheduled for October 14. This data could influence expectations for Federal Reserve policy and shape risk appetite across financial markets.
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