As a potentially record-breaking El Niño for the modern era is forecast for 2026–2027, a key question is how much of the resulting global temperature response to such an unprecedented regime can be attributed to the El Niño-Southern Oscillation (ENSO) relative to the background anthropogenic warming trend over late 2026 and 2027. To explore this question, we introduce TESR, a Ridge regression-based model designed to quantify the influence of ENSO on Global Mean Surface Temperature Anomalies (GMSTA) and to produce probabilistic projections conditioned on ENSO, providing a simple and reproducible way to update these estimates as new seasonal forecasts become available. The model performance was evaluated through out-of-sample walk-forward validation and retrospective probabilistic forecasts. Using Niño 3.4 index as a delayed predictor of the GMSTA response while allowing a non-linear sensitivity that can evolve with the background warming trend, TESR achieves a 47.4 % reduction in retrospective RMSE against a simple ENSO Ordinary Least Squares (OLS) trend benchmark and a Brier Skill Score of 0.798 against per-origin climatology. Initialized with the August C3S multi-model seasonal forecast, TESR projects a GMSTA remaining around +1.9 °C above pre-industrial levels throughout January-May 2027, the period during which the influence of El Niño on global temperatures is simulated as being at its peak, with a median peak of +1.91 °C in March 2027. The model further estimates a 23–24 % likelihood of temporarily exceeding +2.0 °C relative to the pre-industrial period during the 2027 spring season, whereas the +1.5 °C Paris Agreement threshold is highly likely to be surpassed for several months, leading to high chances that 2027 ends up as the warmest year ever recorded since instrumental records began, ranging from +1.57 to +1.92 °C above pre-industrial levels under the August initialized model ENSO trajectory hypothesis. When accounting for the historical underestimation of the strongest temperature peaks by TESR, this probability rises to 45–60 % in sensitivity tests. An ENSO-neutral counterfactual indicates that El Niño substantially increases the probability of crossing both thresholds, though the background warming trend remains the primary driver of the projected anomaly. Since the projected ENSO amplitude used to drive the model for 2026–2027 exceeds the historical range used for model training, we suggest a careful interpretation of the results that should be viewed as experimental rather than a definitive short-term climate forecast.