Predictive History

About Predictive History

Predictive History, operating under the handle @predictivehistory on YouTube, is a content channel situated within the education category. With a total subscriber base of 2,920,000 and a cumulative view count of 106,498,933 across 192 published videos, the channel functions as an analytical exploration of historical patterns and predictive modeling. The creator’s stated mission is inspired by Isaac Asimov’s 'Foundation' series, specifically the concept of 'psycho-history'—a fictional science aimed at understanding the past to forecast future human behavior. The channel’s editorial focus is structured around three core inquiries: identifying the paradigms that best explain world history, applying historical lessons to contemporary global predicaments, and determining the extent to which future events are mathematically or theoretically predictable. By bridging the gap between theoretical sociology, historical data, and speculative science, Predictive History provides a structured framework for viewers interested in macro-historical analysis. The channel does not currently focus on secondary categories, maintaining a singular commitment to educational content that challenges traditional historiography. As a Canadian-based entity, the channel maintains a global reach, though specific language metrics remain unverified. The content serves as a digital archive for those seeking to apply rigorous modeling to historical narratives, positioning the creator as a significant voice in the educational space on YouTube.

Predictive History's estimated sponsorship rates

The estimated cost for a sponsored video integration on Predictive History ranges from $5,445 to $8,470, with a typical valuation of $6,655. These figures are derived from an algorithmic analysis of the channel’s performance metrics, specifically leveraging a niche CPM band of $18 to $28, with an anchor value of $22. The valuation is heavily influenced by the channel's high-confidence average view count of 302,508 per video. Several factors contribute to this pricing structure relative to other creators in the education sector. First, the channel’s 'mega' audience tier classification indicates a substantial reach, which commands a premium in the educational niche where viewer retention is typically higher than in entertainment-focused categories. Second, the nature of the content—which requires significant research and intellectual synthesis—suggests an audience that is highly engaged and likely to have a higher propensity for conversion on complex products, such as software, educational platforms, or analytical tools. While the subscriber count of 2,920,000 provides a baseline for reach, the specific CPM band is adjusted based on the high-intent nature of the educational content. Advertisers pay for the creator’s ability to synthesize dense historical data into accessible formats, which effectively filters for a demographic that values long-form, information-dense media. For a detailed breakdown of the variables used to calculate these figures, please refer to our /methodology page.

Who should partner with Predictive History?

The audience for Predictive History is primarily composed of individuals interested in macro-history, political science, and predictive modeling. Given the channel’s focus on historical paradigms and future forecasting, the viewer demographic likely overlaps with sectors such as fintech apps, online brokerages, and personal-finance education platforms, where analytical thinking and long-term planning are core values. The channel’s content strategy attracts a sophisticated viewer who is accustomed to high-level intellectual discourse, distinguishing it from broader educational channels that cater to general knowledge or K-12 curriculum. When comparing the channel to peers within the education niche, such as QuizKnock—which focuses on intellectual competition and trivia—Predictive History occupies a more specialized, theoretical space. While creators like Let's Crack UPSC CSE Hindi or Chandra Institute Allahabad cater to specific regional academic testing requirements, Predictive History appeals to a broader, interest-based global audience that is not tied to a specific localized syllabus. This suggests that brand partnerships involving complex, high-involvement products are more viable here than for channels strictly focused on standardized test preparation. The audience is characterized by a high degree of intellectual curiosity, making them a target for brands that prioritize educational authority and long-form engagement over short-term, impulse-driven consumerism. The channel’s ability to maintain a consistent subscriber base of 2,920,000 indicates a loyal following that values the creator’s specific methodology and thematic consistency.

Predictive History's growth and performance

Predictive History has demonstrated consistent growth over the observed period. Data tracking began on August 8, 2026, at which time the channel held 2,750,000 subscribers. By the latest snapshot on October 3, 2026, the subscriber count reached 2,920,000. This represents a total increase of 170,000 subscribers over a span of 56 days. This growth trajectory indicates a steady acquisition rate of approximately 3,035 subscribers per day during the tracked interval. While we do not yet have historical view-count data to correlate this subscriber growth with specific video releases, the consistent upward trend in the subscriber base suggests that the channel’s content continues to resonate with its target audience. The current growth rate places the channel in a stable position within the 'mega' tier, reflecting a sustained interest in the creator’s specific niche of historical and predictive analysis.

How our pricing estimate works for Predictive History

The valuation and performance metrics provided for Predictive History are generated through a proprietary algorithmic model. This model calculates the estimated cost for brand integrations by multiplying the channel’s subscriber count and verified average view counts by niche-specific CPM (Cost Per Mille) bands. For this channel, we utilized a CPM band of $18–$28, which is calibrated based on historical performance data within the education category and the creator's specific audience engagement levels. The 'typical' rate provided is an estimation of the market value for a standard YouTube video integration, accounting for the creator’s reach, audience tier, and the high-intent nature of the content. These estimates are intended to provide a standardized benchmark for comparison across the creator economy. For a comprehensive explanation of the variables, multipliers, and data-weighting processes used to arrive at these figures, please consult our /methodology page.