Post-therapy pneumonitis (PTP) is a relevant side effect after thoracic radiotherapy (RT) and immunotherapy with checkpoint inhibitors (ICI). The impact of the combination of both is unclear. We aim to improve risk estimation by prediction of PTP with and without ICI therapy. To analyze the influence of different fractionation schemes, the value of voxel-wise 2 Gy equivalent dose (EQD2) is investigated. Clinical data from 100 patients who received fractionated RT (single dose ≤ 3Gy) RT were collected. 36 patients received additional ICI therapy. PTP of all grades were monitored. Planning Computed tomographies (CTs), segmentations and 3D dose data were extracted and converted to EQD2. Dosiomics and radiomics features were extracted using 1000-fold bootstrapping using Pearson intercorrelation and the Boruta algorithm for 5 single and 4 combined predictive models. Machine learning algorithms (random forest (rf), logistic elastic net regression, support vector machine, logitBoost) were trained and tested using a 5-fold nested cross validation approach and Synthetic Minority Oversampling Technique resampling in R. Analysis was performed using the area under the receiver operating characteristic curve (AUC) on the test sets of the outer folds. All investigated models predicted PTP better than random (AUC>.5) (Table 1). Dosiomics+Radiomics models based on EQD2 using rf classifier resulted in the highest predictive performance (AUC = .83 (95% Confidence Interval .83-.84)) and performed worse on physical dose data (AUC = .72 (.71-.73)). For single models, radiomics and dosiomics achieved the best prediction (AUC = .73 (.72-.74), AUC = .8 (.79-.81)) for physical dose and EQD2, respectively. Clinical factors and ICI therapy (AUC = .6 (.59-.62)) had minor impact on PTP prediction. Table 1: AUC and 95% confidence intervals (CI) for all investigated Machine Learning models for EQD2 and physical doses (D). Dosiomics+Radiomics machine learning models have strong capability of PTP prediction and could contribute to pre-treatment decision making. Fractionation schemes should be considered for dose-based prediction strategies. Additional ICI therapy has limited impact on PTP prediction.